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In this paper, an anti-unwinding adaptive robust backstepping control law is proposed to solve the attitude control problem of rigid spacecraft with external disturbances and inertia uncertainties. A new variable based on hyperbolic sine functions is designed to prevent the unwinding phenomenon, and then a novel robust backstepping controller is developed. Initially, a nonlinear tracking law is designed to obtain the desired angular velocity and to ensure that the attitude maneuvering system could have two equilibrium points. Subsequently, an adaptive robust control law is devised, which incorporates the adaptive estimation method to update the inertial parameters in real-time. Moreover, the bounded external disturbances are taken into account in the design of the control law, and thus the robustness of the attitude control system is improved. Furthermore, the global asymptotic stability of the attitude control system is verified by the Lyapunov-Krasovskii theorem. Finally, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed control law, as well as the anti-unwinding characteristics are perfectly validated during the attitude maneuver of rigid spacecraft. [ABSTRACT FROM AUTHOR]

This study focuses on enhancing the control precision and efficiency of a two-degree-of-freedom (2-DOF) space manipulator used for active space debris removal. The unpredictable space environment introduces large uncertainties, which introduces unique challenges beyond the capabilities of a standalone computed torque controller and degrades control performance. To address this problem, a robust controller is developed, integrating traditional techniques such as sliding mode and computed torque control with a Neural Network framework. This synergy leverages both methods' strengths—conventional controls' accuracy and Neural Network's adaptability. The integration of Neural Network-based sliding mode control complements the robustness of computed torque control by actively mitigating uncertainties and disturbances inherent in the space environment. The 2-DOF manipulator's state variables model the system dynamics, necessitating accurate relative motion estimation between the manipulator and debris. The global asymptotic stability of the developed algorithm is demonstrated through the Lyapunov theorem, guaranteeing error convergence to zero. The convergence, stability, precision, tracking errors, and responsiveness of the controller have been analysed and validated by the MATLAB Simulink simulations. The novel approach's performance effectiveness is substantiated by numerical simulations and a comparative analysis with conventional computed torque control. Outcomes highlight the superior precision and efficiency in manipulator tracking the trajectory, validating the integrated controller's potential for successful active space debris removal. • Neural network-based sliding mode computed torque control (NSMCTC) approach ensures precise space manipulator position tracking. • NSMCTC reduces chattering and improves convergence for enhanced trajectory control in dynamic space environments. • Lyapunov stability theorem validates uniform and ultimate boundedness, ensuring global asymptotic stability. • Self-learning capability and low computational complexity distinguish NSMCTC from traditional computed torque control methods. • Potential applications extend to spacecraft manipulator attitude control, offering adaptability for safe debris capture in multidimensional dynamics. [ABSTRACT FROM AUTHOR]

• The 6-DOF attitude-orbit coupled model of SFF is established. The model has no redundant state and can be achieved globally without singularity. • A FxTDO is developed to estimate the external disturbance. Any prior knowledge of the disturbance is not required. The estimation error of the disturbance can converge to zero in fixed time regardless of the initial states. • A composite control scheme which consists of the NFFTSM surface and a feed-forward term based on the FxTDO is proposed such that each follower spacecraft can track the desired positions and attitudes in fixed time. This paper presents a distributed fixed-time control protocol for 6-DOF(degree-of-freedom) attitude-orbit coupled spacecraft formation flying with external disturbances. Firstly, the 6-DOF attitude-orbit coupled dynamics is established. The communication topology between the spacecraft in the formation is described by a directed graph. Secondly, a fixed-time disturbance observer (FxTDO) is designed to ensure that the estimation errors of the unknown external disturbances can converge to zero in fixed time. Thirdly, based on non-singular fixed-time terminal sliding mode (NFFTSM) surface, the fixed-time coordination control protocol is proposed combined with the fixed-time disturbance observer, which can guarantee that each spacecraft can track their desirable positions and attitudes in fixed time. The stability of the closed-loop system is proved through Lyapunuov method. Finally, simulation results for a formation with one virtual leader and five followers demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The agility of satellites equipped with large and flexible structures, such as solar panels or antennas, poses a significant challenge due to the influence of elastic dynamics on attitude motion. This results in reduced pointing accuracy and dimensional stability of the payload. To address this issue, an Active Collocated Attitude Control (ACAC) system has been developed, utilizing actuators for both the elastic dynamics (distributed piezoelectric devices) and attitude control (ON-OFF thrusters). In the initial phase of the project, the algorithm underwent extensive verification using a high-fidelity numerical model of a spacecraft with two very-low frequency flexible solar panels and a payload consisting of two long booms and a transversal antenna's reflector. The paper focuses on the second phase of the project, which revolves around the experimental verification of the control architecture concept. To achieve this, a scaling procedure employing the dynamic analogy approach was implemented to determine the design parameters of a free-floating platform equipped with elastic appendages. This ensured that the resulting elastic multibody system displayed similar dynamic behavior to the full-scale satellite. Based on the scaling parameters, a test rig was manufactured, and actuators and sensors were optimally positioned. The performance of the ACAC system was then compared to that of traditional benchmark controllers. The results show that the ACAC system demonstrates superior capabilities in performing fast slew maneuvers without developing unstable interactions with the elastic dynamics. • Agile maneuvers of large satellites could excite rigid-flexible interactions. • A robust control of attitude and elastic dynamics is implemented to improve agility. • Performance obtained with numerical models is verified with scaled-down test-rig. • Simplified dynamic equations are developed to determine scaling conditions. • Experimental results of the robust control are consistent with simulation. [ABSTRACT FROM AUTHOR]

This paper concentrates on robust attitude control issues for spacecraft formation in gravitational-wave detection missions. Notably, with the large-scale communication delays brought by the million kilometers-scale inter-satellite distance, the exponential convergence of the closed-loop delayed system is firstly achieved via a new delay-dependent nominal attitude coordinated control scheme. Then, a finite-time disturbance observer is deployed to reconstruct the unknown lumped disturbance from internal uncertainties and the external environment. Meanwhile, an integral sliding manifold is embedded in the delay-dependent attitude controller for superior systems' robustness. Finally, two simulation examples illustrate the feasibility and effectiveness of the proposed attitude control strategy for in-orbit gravitational-wave detection spacecraft systems. • Spacecraft formation attitude control in gravitational-wave detection is studied. • Large-scale communication delays (LCD) among formation members are firstly modeled. • An attitude coordinated controller is put forward to handle the LCD. • An integral sliding manifold with disturbance observer is embedded for superior robustness. [ABSTRACT FROM AUTHOR]

A pressure control method that incorporates parameter adaptation has been devised for the pressure control system of pintle solid rocket motors, which exhibit notable nonlinearities and uncertainties in parameters. Firstly, the mathematical relationship between pressure and pintle displacement is derived using the zero-dimensional interior ballistic model., and the state space equation is deduced by incorporating the dynamics of motor inertia load. Secondly, by capitalizing on the robustness of robust control, the parameter identification capabilities of adaptive control, and the rigor of Lyapunov stability theory, the proposed approach enables precise control of the pintle position while effectively addressing uncertainties, thereby enhancing the overall performance and stability of the system. Finally, the aforementioned theoretical framework has been validated through rigorous numerical simulations. The findings demonstrate a notable enhancement in the pressure response speed of the adaptive robust controller, with improvements of 10.01 % and 13.16 %, 0.03 % and 1.54 %, 0.06 % and 22.39 % in different orders of magnitude of free volume as compared to the robust controller and PID controller, respectively. Moreover, it is evident that the adaptive robust controller relies on the accuracy of the model. The applied controller demonstrates notable advantages in terms of stability, robustness, and accuracy, thereby substantially enhancing the overall performance of the pressure control system. • The state space equation for the pressure of the pintle solid rocket motors is derived. • The pressure dynamics equation and the motor inertial load equation are combined. • An adaptive robust controller with respect to pressure is designed. • The controller response laws for various free volumes, pressure index and characteristic velocity are obtained. • The adaptive robust controller exhibits a higher dependence on model accuracy is observed. [ABSTRACT FROM AUTHOR]

In this paper, a delayed distributed proportional control is developed for a class of multiple-input-multiple-output systems in order to reduce the effects of external disturbances and uncertain dynamics. The system under consideration is a three degrees-of-freedom planar robot, consisting of an active joint driving the first link and passive flexible joints for the second and third links. The control challenge for this system is to drive the flexible arm around the desired setpoint or trajectory by controlling the first link. Actually, by using a specific Lyapunov-Krasovskii storage functional associated with a constrained optimization problem, the robustness of the proposed proportional retarded control action is achieved. This analysis, together with the attractive ellipsoid concept allows to conclude with Ultimately-Uniformly-Bounded stability. The closed-loop control algorithm is tested in numerical simulation and a comparative study with some existing recent control schemes based on the performance error is presented. • The proposed control scheme belongs to a class of multivariable proportional time delay distributed controller. • After finite time the trajectories of a flexible manipulator stay within reduced size attractive ellipsoid. • Ultimate Uniformly Bounded Stability of the controlled system is demonstrated by using a Lyapunov-Krasovskii functional. • The proposed algorithm can also be adapted for a class of nonlinear uncertain/disturbed multivariable output systems. • A sufficient condition to guarantee the feasibility of specific Bilinear Matrix Inequality is presented. [ABSTRACT FROM AUTHOR]

ESA Solar Orbiter was launched from Cape Canaveral in collaboration with NASA on the February 10, 2020 to start its journey around the Sun, with the commissioning phase ending in April 2020. After commissioning, ESA set a tighter pointing requirement goal to further improve the performance in Fine Pointing Mode, in preparation of the upcoming start of Science Phase. The first part of this paper outlines the end-to-end process which allowed - in just six months – to update the Fine Pointing Mode Design, re-tune the controller with refined assumptions taken from flight data and robust methods and execute full validation of the new AOCS Software on the Avionics Test bench at Airbus Defence and Space. The second part of the paper describes the upload in flight of the new Software and the analysis of the on-orbit pointing performance, which showed a significant improvement with respect to the previous one, thus contributing to the success of the Mission's scientific goals. • Solar Orbiter Payload Instruments required a better pointing jitter performance (Relative Pointing Error) after launch • Root cause analysis on flight telemetry to identify driver contributors to pointing error • Fine Pointing Mode controller design and tuning updated with refined inputs based on flight data and with robust control methods • Controller uploaded in flight significantly improved the Spacecraft pointing performance [ABSTRACT FROM AUTHOR]

• A novel I&I adaptive scheme is presented. • Immersion and invariance based adaptive terminal sliding mode control is proposed. • Immersion and invariance based adaptive terminal sliding mode control with saturation compensation is presented. This work investigates attitude control of spacecraft with uncertainties and input saturation. An immersion and invariance based adaptive robust control (IIARC) is proposed to improve tracking performance of spacecraft. The proposed approach consists of an immersion and invariance (I&I) estimator, a robust adaptive law, and a terminal sliding mode control (TSMC). The continuous fast TSMC is designed to stabilize the system and obtain fast convergence rate. To estimate the disturbances and uncertainties, I&I methodology is introduced into the proposed approach. The robust adaptive law is applied such that the prior information of disturbances is not required. IIARC with saturation compensation (IIARCSC) is presented to reduce the effect of input saturation on the attitude tracking of spacecraft. It is proved that the developed approach could guarantee the finite-time convergence (FTC). Extensive comparative simulations demonstrate the effectiveness of the presented scheme. [ABSTRACT FROM AUTHOR]

This paper addresses the control problems of distributed attitude coordination for multiple flexible spacecraft based on the feedback of inertial vector measurements. It is assumed that the angular velocity information is not available, and the modal variable cannot be measured. The orientation error model with vector measurements is introduced. And then the distributed attitude synchronization control scheme is presented without actuator faults or disturbances. It is guaranteed that the desired equilibrium is locally asymptotically stable and the undesired equilibrium is unstable. Meanwhile, the domain of attraction is given by inequality constraints. In the case that there exist actuator faults and external disturbances, a robust fault-tolerant control strategy is developed to realize attitude synchronization. The hyperbolic tangent function in place of sign function is adopted to eliminate external disturbances. Meanwhile, the adaptive laws are proposed to estimate actuator faults. The salient feature of these control approaches is that no modal variable observers are utilized and the control schemes are robust to the inertia uncertainty of spacecraft. Finally, numerical simulations are implemented to manifest the validity of the presented control schemes. [ABSTRACT FROM AUTHOR]

• The TM capture is first reformulated to nonlinear quadratic optimal control. • The high-efficiency NMPC with robustness and optimality is proposed for TM capture. • The mixed state and control constraints are integrated into the robust optimal control. • The proposed method guarantees the computational efficiency. This paper presents a nonlinear high-efficiency model predictive control (NHMPC) with constraints designed for the test mass (TM) capture phase of the drag-free satellite about gravitational wave observatory. To avoid collisions between test mass and satellite cavity, TM capture is the essential technology for drag-free satellite. Test mass is located inside an electrostatic suspension and locked by a clamp mechanism initially. The test masses are released with high initial offsets and velocities when the mechanism is retracted. The purpose of this phase is to guarantee the TM to be positioned at the cage center and attitude aligned with the local cage frame. Due to the low actuation authority of electrostatic suspension along with critical initial offsets and velocities, it is a challenging task to design the attitude and translation control schemes with simultaneous consideration of system performance and energy consumption. For the problem given above, the TM capture can be reformulated into a nonlinear quadratic optimal control problem with the state and input constraints. A nonlinear model predictive control (NMPC) structure is also designed to handle the noises by forming a closed loop. This control framework can realize optimality and robustness in a compromise. To improve the speed of solving high-dimensional nonlinear optimal control online for MPC, the indirect Chebyshev pseudospectral method with constraints is employed. The convergence and stability of the control loop are analyzed. Simulation examples show that the feasibility and performance of the designed control loop are verified compared with the existing methods and computation times in the millisecond range can be achieved. [ABSTRACT FROM AUTHOR]

• The preview tracking controller for interconnected continuous-time systems with parameter uncertainties is designed. • The previewable information is integrated to the states of error system, which is a new framework of preview control. • The performance index function and performance signal are constructed to research the influence of disturbance. • The proposed preview controller can make the tracking quality improves as the preview length increases. This paper designs a decentralized robust preview tracking controller for interconnected continuous-time systems with parametric uncertainties. The uncertain error system, which is composed of the derivative equation of the states, the tracking error dynamics, and the available future reference dynamics, is constructed. Then, a cost function is introduced to evaluate the tracking quality. Meanwhile, a performance signal is defined to discuss the influence of disturbances on the tracking performance. Based on the above operations, the considered tracking control is converted to the H-infinity control of the uncertain error system. The sufficient conditions which guarantee that the closed-loop system is asymptotically stable with H-infinity disturbance attenuation are derived. Further, the decentralized preview controller is obtained with the help of the linear matrix inequality (LMI). The result is applied to double-parallel inverted pendulum system and 3-interconnected machine power system. Numerical simulation demonstrate that the suggested preview controller can make the output track the reference signal, and the tracking quality be improved as the preview length increases. [ABSTRACT FROM AUTHOR]

The integration of BeiDou System (BDS) and the fifth generation (5G) system is expected to provide positioning services with high accuracy and reliability. In particular, as an important technique in the 5G system, device-to-device (D2D) communication enables the cooperative positioning for the mobile users (MUs) to offer a large number of redundant measurements, where the received signal strength (RSS) measurement can be exploited due to its easy access and cost-efficiency. However, the RSS measurements cannot be accurately modelled to reflect the propagation distances. In this paper, a robust BDS/5G integrated positioning scheme based on the resilient observation model is proposed. Specifically, the extended Kalman filter (EKF) is exploited to recursively integrate the BDS pseudorange and RSS measurements to estimate the unknown position parameters. We establish a resilient observation model based on the signal propagation model in the 5G network, through which the errors in the RSS measurements are compensated for by the BDS pseudorange measurements. Moreover, the effects of the abnormal errors in both kinds of the measurements are controlled by the robust estimation through automatically adjusting the weights of the measurements. Numerical results show that the proposed resilient observation model can correct part of the errors in the RSS measurements and results in higher positioning accuracy compared to the positioning based on the RSS measurements or the direct integration of both the BDS pseudorange and RSS measurements in different scenarios. The proposed algorithm also outperforms the positioning based on the BDS pseudorange measurements when the visible satellites are not sufficient. [ABSTRACT FROM AUTHOR]

This paper deals with the nonfragile fuzzy tracking control technique of a spacecraft subject to external disturbances and control gain uncertainties. First, the Takagi–Sugeno (T–S) fuzzy model of the tracking error dynamics is newly derived. Unlike the existing studies, we assume that the controller output is norm bounded and its gain matrix is perturbed because of the aging of the actuator. Next, a fuzzy disturbance observer (DOB) estimating the external disturbance is constructed to enhance the robustness of the control system. Then, a fuzzy controller feeding back the estimated disturbance is designed to attenuate external disturbances. In addition, we establish the linear matrix inequality (LMI) conditions, by which both the H ∞ disturbance attenuating performance and the asymptotic stabilization are guaranteed. From the solution to the LMI conditions, we obtain the controller and DOB gain matrices. Finally, a simulation example validates the disturbance estimation and tracking performance of the proposed method. [ABSTRACT FROM AUTHOR]

Quadrotors are extremely agile UAVs with many unknowns regarding their moment of inertia, drag coefficients, and mass. Aside from aerodynamic turbulence, the quadrotor has a high level of nonlinearity due to its underactuated mechanical system. These last two factors cause issues that necessitate adaptive and robust control. A hybrid robust nonlinear control approach for a quadrotor is described in this research paper. To address the quadrotor trajectory tracking problem, a combination of backstepping and sliding-mode approaches based on proportional integral derivative (PID) surfaces is developed, with the Lyapunov method used to evaluate the control system's stability. The adaptive technique, in conjunction with sliding-mode and super-twisting algorithm, is then investigated in order to reduce the chattering impact of sliding mode control and estimate the various controller parameters. Super-twisting adaptive backstepping PID sliding mode approach for the quadrotor rotational and translational subsystems is presented to reduce error convergence time and improve speed tracking performance. The simulation results under various scenarios (parameters uncertainties under Gaussian random disturbances, constant and time-varying external disturbance) are given to demonstrate the efficacy and practicability of the proposed control. A comparative analysis is performed with different developed controllers using the performance of the integral of absolute error and the integral of the absolute value of the derivative of the control inputs to demonstrate the superiority and effectiveness of the designed control technique. [ABSTRACT FROM AUTHOR]

In this paper, a fractional neural integral sliding-mode controller based on the Caputo-Fabrizio derivative and Riemann–Liouville integral for a robot manipulator mounted on a free-floating satellite is proposed and developed. The mathematical model is obtained by using the Euler–Lagrange formalism and generalized through the Caputo-Fabrizio derivative. The conventional neural integral sliding-mode controller reported in the literature were also developed to make a comparative analysis between both controllers. The controllers are tuned using a swarm intelligence algorithm. External disturbances are also considered. Simulation results show the superiority and robustness of the proposed control system for trajectory tracking tasks through the root-mean-square error. Additionally, two additional reference trajectories were considered. In this sense, the numerical simulations were done by using the same orders and gains, showing the robustness of our fractional-order control strategy under different operating conditions. Further, the proposed controller uses the fractional derivative in the sense of Caputo-Fabrizio which has not been used enough in the area of robotics, so this is a start to analyse the contributions that arise when using said derivative in this robotic. [ABSTRACT FROM AUTHOR]

• A new mathematical model for rubber–tyred gantry cranes is developed considering the elastic structure. • Two advanced sliding mode controls are proposed to validate dynamic model. • Experiment shows the sufficient accuracy and effective application of modeling and control to cranes. A gantry crane holds strict underactuation and elastic multibody structure, and thus faces challenges in control system design. For model–based control, we develop a three–dimensional dynamic model of rubber–tyred gantry cranes considering the distributed mass and bending deformation of gantry. Such modelling hybridises the lumped model of trolley–bridge–payload motions and continuous model of gantry vibration. We consider a complex operation in which three motors composed of travelling trolley, pushing bridge and hoisting container run simultaneously. We propose two versions of the robust controller, namely, dynamic sliding mode and fast terminal sliding mode for tracking the three motions, eliminating swings of container, and reducing the bending vibration of elastic gantry. Simulation and experiment reveal precision and effective application of our crane modelling to control approaches. The control system effectively tracks and stabilises all outputs and achieves robustness when a crane suffers from the structural and parametric uncertainties. [ABSTRACT FROM AUTHOR]

This article presents a robust coalitional model predictive control (MPC) approach where neighboring agents negotiate the bounds of their coupling variables. Also, the control variables of each agent are divided into a private part that is locally optimized, and a public part that is controlled by the corresponding neighbors. Under certain conditions, the agents communicate to update the bounds that determine the constraints on these private and public variables. Moreover, the mutual disturbances induced by coupling are considered using a tube-based approach, guaranteeing recursive feasibility and stability of the closed-loop system. The proposed method is tested on a simulated eight-input coupled tank benchmark to illustrate its benefits. • Splitting the global optimization problem by clustering model predictive controllers. • Coupling variables decomposition into multiple versions distributed among agents. • Event-based communication to negotiate the size of the input constraint set. • Mutual disturbances are considered using a tube-based approach. • Feasibility and stability of the closed-loop system are guaranteed. [ABSTRACT FROM AUTHOR]

This article presents the control of Soil moisture, Nitrogen, and Salt content in soil using a robust control technique to maintain a desired quality of soil in a drip irrigated field. The control of this multi-variable system is accomplished by adopting two possible control structures namely (i) a decentralized controller backed by a feed-forward controller (ii) a diagonal centralized de-coupler along with a diagonal controller. The controllers are designed using quantitative feedback theory. The efficacy of the proposed techniques is validated through numerical simulations. A comparative study among the two methods reveals that the former performs better than the later. Another comparative study shows that the proposed controller outperforms some of the reported works. • Control of Soil moisture, Nitrogen and Salt content in a drip irrigated field. • A 3 × 3 uncertain model is derived from physical laws and practical data. • De-centralized QFT along with feed-forward controllers is proposed. • Centralized decoupler with diagonal QFT based controllers is proposed. [ABSTRACT FROM AUTHOR]

Navigation and proximity to non-cooperative targets have garnered the interest of both academia and industry. This paper proposes a new space operation concept that would enable two CubeSats equipped with only optical sensor to achieve autonomous and robust proximity with uncooperative satellites. This is a novel strategy for distributed spacecraft missions and applications. Because optical sensors are lightweight and therefore reduce reliance on external measurement sources, the case for their use is compelling. Designing robust guidance and control algorithm is the greatest challenge for optical sensors because relative distance information is unavailable, whereas range information is required for safe proximity. The purpose of this paper is to propose a novel concept in which two CubeSats cooperate and share angle measurement data to approach uncooperative targets despite their maneuverability. This paper introduces a new guidance scheme for proximity operations, namely cooperative augmented proportional navigation (CAPN). Modern control law is applied along line-of-sight (LOS) while classical proportional navigation is applied in the normal direction of LOS. By measuring only elevation and azimuth angles between each chaser and the target, the algorithm can account for a maneuvering target. The cooperative scheme offers estimation-based distance measurement, which enhances the observability of angle-only navigation. Target's maneuverability and different control parameter settings have been considered in simulation scenarios. The degree of observability (DOO) is then introduced as the quantitative observability analysis metric to validate the effectiveness of the guidance scheme and precision of the estimation. The results of simulations have demonstrated that the CAPN proposed in this paper is capable of completing challenging proximity missions. [ABSTRACT FROM AUTHOR]

This paper addresses the post-fault selection of an actuators configuration for flow-based networks with back-up components. The proposed reconfiguration methodology consists of an offline and an online phase. On the one hand, an offline analysis looks for the minimal configurations for which the economic cost of the (best) steady-state trajectory that can be achieved using a robust model predictive control (MPC) policy is admissible. On the other hand, at fault detection time, an online search for the best actuators configuration to cope with the transient induced by the fault is conducted in the superset of each minimal configuration calculated offline. With this strategy, the final new configuration is computed by sequentially solving a set of mixed-integer programs whose constraints are derived from single-layer robust MPC schemes coupled with local controllers designed for the a priori minimal configurations identified offline. A portion of a water transport network is used to show the performance the proposed solution. • Methodology for post-fault actuators configuration selection in flow-based networks. • Offline search for confs. with an economically admissible steady-state trajectory. • Online selection of the optimal configuration to deal with the fault-induced transient. • Simulation results show good performance in a large-scale water transport network. [ABSTRACT FROM AUTHOR]

This paper proposed a novel underactuated control scheme to deal with the rotational deployment of a dual-body tethered satellite system without using tangential force acting on the tether. To describe the spin motion of the system during tether deployment, the parent satellite is modeled as a rigid body. An underactuated robust control framework is developed to govern the rotational deployment of the system in the presence of disturbances and model uncertainty. The adaptation update laws are designed to adjust the gain of the robust term of the controller, thereby improving the anti-interference ability of the system to cope with the perturbations stimulated by the spinning of the parent satellite. The underactuated rotational deployment controller theoretically guarantees the stability of motion of the entire system, that is, the uniformly ultimate boundness of the closed-loop control system can be strictly proven using Lyapunov theory. Finally, simulations are performed to validate the effectiveness of the proposed control scheme. • Rotational deployment strategy for a tethered satellite system is investigated. • The underactuated methodology governs the deployment process without resorting to tangential forces. • An adaptive-gain based robust controller improves the anti-interference ability of the system. [ABSTRACT FROM AUTHOR]

When controlling cyber–physical systems via consensus algorithms, the robustness issue is of paramount importance because of model mismatching and/or disturbances that generally modify the Laplacian flow dynamics associated to the overall network, compromising the possibility to achieve any expected, orchestrated emergent behavior. To face this issue, the Variable Structure Control (VSC) approach has recently been shown to be an effective tool in designing control protocols over networks, providing robustness and often yielding finite-time convergence. Moreover, VSC further enables the decoupling of simultaneous control objectives where reaching a consensus state is only part of a more complex task, for instance as it happens in distributed optimization. Thus motivated, this paper overviews, from a tutorial perspective, some selected recent advances in the application of VSC with Sliding Modes to design robust consensus controllers in both the leader-less and the leader-following settings. Efforts are also made to unify the notation and to discuss the theoretical foundations of the nonsmooth analysis tools at the basis of their design for a wide readership unfamiliar with these problems and formal tools. To this aim, examples supporting the treatment, and numerical simulations, are given and discussed in detail. Finally, hints for future investigations along with some current open problems are provided. [ABSTRACT FROM AUTHOR]

• A resilient GESO based MRC control is designed to tackle the uncertainties and disturbances of turbofan systems. • The concise design of the control is developed by imposing the estimated disturbance on the control input channel. • The developed controller makes the state of the system to follow the given reference signal with accurate tracking. • Additive and multiplicative fluctuations are considered while designing the controller for better tracking performance. • The design procedure of the controller gain matrices are developed in the framework of linear matrix inequalities. The intention of this work is to analyse the issues of multiple disturbance estimation and rejection as well as robust tracking control design for turbofan systems subject to input gain perturbations. A standard generalized extended state observer is developed to estimate both the state disturbances and output measurement disturbances, simultaneously. Therewith, a modified repetitive controller is utilized with generalized extended state observer to track the states of the turbofan system accurately. Then, a new composite control strategy is developed by incorporating the estimates obtained via generalized extended state observer in modified repetitive controller to attenuate the effect of disturbances. Based on the pole placement technique, the observer gain is calculated and in accordance with Lyapunov stability theory, a set of sufficient conditions which ensures the robust asymptotic stability of the considered turbofan system is derived in the form of linear matrix inequalities. Moreover by offering the numerical examples with simulation results, the superiority of developed control strategy is validated. [ABSTRACT FROM AUTHOR]

An AM2 model modification is proposed by including the parameter identification and a robust feedback control synthesis. The contribution is shown by experimental proof-of-concept. The AM2 model is modified with the aim of including the CODs changes in the effluent near the steady state with the inlet CODt concentration changes at a fixed flow rate. The parameter identification is experimentally implemented on-line and computationally performed via the Levenberg–Marquardt algorithm. To this end, an experimental set-up was carried out each from a two-stage biomethane production process stage as an instrumented and automated bioreactor. Afterward, robust feedback control is implemented for each stage. For the first stage, the VFA productivity maximum is defined as the control goal whereas the biomethane maximum flow is the aim on the second stage. The feedback control is robust against kinetics and parametric uncertainties such that the biogas production reaches biomethane maximum production. In this sense, the contribution shows the biomethane production can be optimized through enzymatic agave bagasse hydrolysate. • Biogas yielding via enzymatic hydrolysate of agave bagasse needs model modification. • A modified model renders an accurate structure for kinetics parameter identification. • A robust feedback control allows us to enhance the biomethane production. • An experimental benchmark shows the concept of enhancing biomethane production. [ABSTRACT FROM AUTHOR]

• A special combination of extended state observer and Kalman filter is proposed to achieve high-precision state estimation and disturbance attenuation for drag-free satellite. • The proposed compound observer can reduce the complex drag-free dynamics into linear models and overcome bandwidth limitation and the high readout noise influence. • GS/T mixed sensitivity H ∞ controllers are designed to enhance robustness based on frequency-domain specifications. • The parameters of the composite drag-free control scheme can be directly determined tuned according to scientific requirements. For future space-based gravitational wave detectors, drag-free control is one of the core technologies to achieve ambitious ultra-quiet-stable requirements. Generally, the high performance of such a drag-free satellite is severely limited by the intrinsic nonlinearities, various noise and limited bandwidth. To overcome these limitations, a dual-loop drag-free control scheme with the merits of simple structure and tuning method is proposed. First, a special combination of Kalman filter (KF) and extended state observer (ESO) is applied in the inner-loop to perform disturbance reduction. The KF serves as noise filtration, while the ESO accepts the filtered measurement signals to achieve better online reconstruction of states and lumped disturbances. Then, GS/T mixed sensitivity H ∞ controllers are adopted in the outer-loop to stabilize the test masses in the cage center. The controllers are tuned based on the sensitivity function and complementary sensitivity function specifications to enhance robustness. Finally, a simulation considering various disturbance models is built to test the effectiveness of the control system. A comparison between three types of controllers reveals the advantages of the proposed method in terms of the disturbance attenuation and control performance. [ABSTRACT FROM AUTHOR]

• A novel nonlinear impulsive time-delay system in fed-batch process is proposed. • The robust parameter identification problem is presented to determine the optimal parameters. • A parallel particle swarm optimization algorithm is developed to solve the identification problem. In this paper, taking the feeding process as an impulsive form and considering the time-delay in fermentation process, we propose a nonlinear impulsive time-delay system to formulate the fed-batch culture in microbial 1,3-propanediol production. For this system, we discuss some important properties of the solution. To determine the optimal time-delay and kinetic parameters in the system, we then present a robust parameter identification model subject to continuous state inequality constraints. By the constraint transcription technique and a penalty method, we transform the robust parameter identification problem to a sequence of optimization problems with only box constraints. On this basis, we propose a parallel Particle Swarm Optimization algorithm to solve the resulting problem. Finally, the numerical results show that the impulsive time-delay system can well describe the fed-batch process and the developed algorithm is highly effective. [ABSTRACT FROM AUTHOR]

This paper aims to determine a time-varying dilution rate of the feed medium which maximizes mean productivity while minimizing both system sensitivity and control cost in glycerol continuous culture. A multi-objective optimal control problem subjected to a nonlinear control system and its auxiliary system is proposed and transformed into a finite-dimensional large-scale multi-objective optimization problem via discretization and time-scaling transformation. A multi-objective competitive swarm optimization algorithm is constructed to solve this transformed problem based on pairwise competition, mutation operation and environment selection. The Pareto front obtained shows the distribution of the optimal target value which indicates the rationality and feasibility of the control system under the approximate optimal strategy. Numerical simulations verify the robustness of the optimal control system and the effectiveness of our numerical solution method. The value of IGD shows the good accuracy and distribution of the proposed multi-objective optimization algorithm. • We propose a multi-objective optimal control problem of glycerol continuous culture. • The multi-objective optimal control problem is approximated by a parameter optimization problem. • A multi-objective competitive swarm optimization algorithm is developed. • Numerical experiments show the effectiveness and applicability of the approach proposed. [ABSTRACT FROM AUTHOR]

Background: Mutant isocitrate dehydrogenase (IDH) in chondrosarcoma produces the oncometabolite 2-hydroxyglutarate (2-HG) and contributes to malignant progression, and is therefore a potential therapeutic target for chondrosarcoma. Robust historical control data are important in clinical trials of rare cancers such as chondrosarcoma in order to show a clear benefit of new drugs. However, it remains controversial whether IDH mutation status is associated with the clinical outcome of chondrosarcoma, and this hinders the development of mutant IDH inhibitors in clinical trials.background METHODS: We investigated the relationship between IDH gene status and clinicopathological data in 38 chondrosarcoma patients from whom frozen tumor samples were obtained at the time of biopsy or surgery. Targeted next-generation sequencing was also performed to compare genetic alterations between patients with and without IDH mutations.Methods Results: The results revealed 15 cases (40%) of heterozygous IDH1 mutations and five cases (13%) of IDH2 mutations. IDH-mutant chondrosarcoma was associated with worse overall survival than IDH-wild-type chondrosarcoma (IDH1/2 Mut vs. IDH Wt, P = 0.006; IDH1 Mut vs. IDH Wt, P = 0.030; IDH2 Mut vs. IDH Wt, P < 0.0001). IDH mutation was also a significant poor prognostic factor both in univariate (P = 0.026) and multivariate (P = 0.048) analyses. Targeted next-generation sequencing revealed that characteristic mutations in chondrosarcoma, including TP53 and COL2A1, were more common in the IDH-mutant group than in the IDH-wild-type group.results CONCLUSION: This study is the first to report in detail the characteristics and clinical courses of IDH-mutant chondrosarcoma patients in Japan. Our data suggested that IDH-mutant chondrosarcomas might have a worse prognosis than that of IDH-wild-type chondrosarcoma, possibly through the more aggressive characters after metastasis. This information will be useful for designing clinical trials of mutant IDH inhibitors for treatment of advanced chondrosarcoma.Conclusion: [ABSTRACT FROM AUTHOR]

This paper investigates the energy-optimal path generating and robust trajectory tracking of satellite formation reconfiguration. First, to minimize the energy consumption during formation reconfiguration, the problem of finding optimal path and control profile is studied. This problem is solved based on the linear Hill-Clohessy-Wiltshire equations and optimal control theory. Second, considering the nonlinearities and disturbances in the dynamics of satellite relative motion, a robust control law based on an uncertainty and disturbance estimator is designed. The primary advantage of this estimator is the relaxation of the assumption on disturbances, and only frequency range is needed. The asymptotic stability of the closed-loop system formed by a robust feedback controller is analyzed. Finally, numerical simulation results are presented to validate the feasibility of the proposed reconfiguration trajectory optimization approach and control strategy. [ABSTRACT FROM AUTHOR]

• The proposed controller can deal with the uncertainties, state constraints, and input boundedness. • This is the first time that such a composite controller for the complex system is designed. • The feasibility and convergence of the hierarchical controlled system is proved. • Comparison simulations are conducted to demonstrate the feasibility of the controller. Multiple aerial vehicles have the potential to transport payload in any direction and with any orientation in Special Euclidean Group. In this article, the control problem of the multiple aerial vehicle transportation system with uncertainties and state/input constraints is considered. The multiple aerial vehicles connect with the load via spherical pairs that coincide with the center of mass of the aerial vehicles. A hierarchical control scheme of such challenging complex systems is proposed. The outer loop is designed by a tube-based model predictive control in order to deal with uncertainties, state constraints and input boundedness, while the inner loop is designed by robust control technique which forces the attitude tracking error of the aircraft into robust invariant set. The attitude tracking error of the inner loop induces a difference between the commanded and the actual equivalent wrench acting on the load. Such difference is treated as the equivalent disturbance of the outer loop to guarantee the fulfillment of the state and input constraints. The hierarchical control structure simplifies the design procedure, while still preserves the convergence and feasibility of the overall controlled system under uncertainties, which are proved strictly in the paper. Numerical simulations on a six-quadrotor transportation system are conducted to demonstrate the performance of the proposed control scheme. A real-world prototype including three quadrotors is developed. The hardware-in-the-loop simulation on the prototype supports the real-time feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

Modern space missions for Earth Observation (EO) purposes often rely on satellites equipped with very large flexible appendages, such as antennas and solar panels, which are demanded to perform agile slew manoeuvres. In most cases, the elasticity of such systems cannot be neglected in the design of the attitude controller, as excessive elastic displacements of the structural elements may compromise their stability and pointing performance. In this scenario, this paper aims at proposing an automated nested optimization framework to simultaneously optimize spacecraft structural and control dynamics, to be applicable to a wide range of flexible spacecraft. The objective of such a co-design architecture is to modify design parameters, at both structural and control levels, to minimize the mass of the spacecraft while maximizing its agility and satisfying imposed requirements. Moreover, as robust multivariable techniques have become more and more applied to ensure satisfactory robust performance margins, this paper's goal is to pose a multi-channel structured H ∞ control architecture in the co-design problem. To guarantee the generality of implementation, a structural design tool (MSC Nastran) is interfaced with a coding environment (Matlab/Simulink) to set-up an autonomous exchange of information between structural and control domains. Starting from an initial definition of the spacecraft material, geometry and control requirements (in terms of loop-shaping transfer functions), relevant parameters are extracted from the structural tool and a linearized dynamic model assembled. Then, a controller is synthetized based on the provided requirements, followed by a verification on the nonlinear plant of the satellite. The procedure is repeated until the stop criteria (based on tolerance and max iterations) is satisfied. Finally, the output of the proposed architecture is obtained as an optimized structural model and robust controller tailored for the satellite dynamics. • The problem of structural/control co-design of flexible spacecraft is addressed. • A general framework interfacing a commercial finite element code and a coding environment is proposed. • The architecture is posed as a nested robust optimization. • A case study composed of a satellite with two flexible solar panels is proposed. • The framework is tested on the satellite non linear model. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-strategy control scheme, which modifies the optimal control problem of robust model predictive control (RMPC) to reduce the on-line computational load or extend the feasible region. The proposed controller is designed to stabilize the system with respect to a subset of the disturbance set. If the disturbance is realized from the rest of the subset, another control strategy is automatically involved to keep the state inside the pre-determined bounded set. The existence of this pre-determined set is proven, and an efficient algorithm is proposed to generate this set. In addition, it is shown that the recursive feasibility and stability of the original RMPC is sustained for the proposed controller. This implies that the proposed method can be applied to a wide range of existing RMPC. Three illustrative examples describe the fundamental ideas and practical advantages. • A multi-strategy control scheme is proposed to reduce the on-line computational load of robust model predictive control. • The extension of the feasibility set of the proposed robust model predictive control is proven. • Both the recursive feasibility and stability of the proposed robust model predictive control is proven. • An efficient algorithm that generates the feasibility set of the proposed robust model predictive control is proposed. [ABSTRACT FROM AUTHOR]

—Currently, most vehicles are generally equipped with roll stability control system or electronic stability control system to improve stability. However, when encountering emergency obstacle avoidance and similar conditions, roll stability control system may compete with path tracking control system for vehicle control, resulting in the inability to balance path tracking and roll stability. Therefore, a closed-loop feedback Nash game collaborative control method is proposed to solve the collaborative problem between the two control systems. Firstly, a fifth-order vehicle model with coupled yaw-roll dynamics is presented, which was extended to a vehicle-road closed-loop model based on lateral position, yaw angle and road preview information. Secondly, the path tracking control system and roll stability control system are regarded as two agents in the dynamic game control process. On this basis, a Nash game collaborative control strategy is designed by fully considering the control interaction between two game agents. Finally, considering the influence of uncertain disturbances, a finite-time minimax robust control strategy is proposed by using minimax optimization theory. Simulation and hardware in loop experiments show that the minimax robust regulator based on Nash game controller can effectively improve the path tracking and roll stability performance of vehicles. Moreover, the regulator improves the robustness of the system when it is subjected to bounded uncertain lateral disturbances. [ABSTRACT FROM AUTHOR]

• A novel active control method is proposed to suppress the milling chatter of thin-walled workpieces. • The non-smooth properties, time delays, multi-modal participation, and varying dynamic characteristics are synthesized together in controller design for the first time. • The combination of robust control and time delay controller enhances the control effect and reduces the control voltage to the single robust control. Chatter phenomena commonly plague the milling process of flexible workpieces, leading to undesirable fluctuations in accuracy and diminished machine efficiency. Limited by complex dynamics of this process, the non-smooth properties, time delays, multi-mode participation, and varying dynamic characteristics have never been considered together in active control. This paper proposes a novel active control method to suppress milling chatter of flexible workpieces by synthesizing these factors together in controller design for the first time. The dynamic model for milling processes of a cantilevered plate, which is regarded as an examined example of flexible structure, is transformed from a time delay differential equation with varying coefficients to a real-time differential equation with constant coefficients by uncertainty transformation. A robust combined time delay control method is tailored for the uncertainty system via combining a robust controller with synthesis method and an active time delay controller. Both simulations and experiments validate the effectiveness and performance advantages. Following the implementation of experiments, the maximum stable milling depth experiences a notable improvement from 0.1 mm to 0.8 mm after control, and is larger than that of 0.6 mm under single robust control. Additionally, under the given milling conditions, the control voltages of robust combined time delay control exhibit a 25 % and 11 % reduction compared to those of the robust control method. The novel combination of a robust controller and time delay controller enhances the control effect and reduces the control voltage. [Display omitted] [ABSTRACT FROM AUTHOR]

The new railway mobility paradigm Virtual Coupling, recognized as one of the most promising solutions to face the ever-increasing demand in railway transportation and the saturation of network capacity, enables two or more trains to virtually couple in a single convoy, hence reducing the headway among them. Within this context, the design of an effective and robust Virtual Coupling control strategy for uncertain nonlinear heterogeneous train convoys, able to simultaneously cope with uncertain nonlinearities and unexpected/unpredictable external factors, is an open challenge in the railway field. This is very crucial for High-Speed Trains, where, due to the high-speed operating ranges, uncertain factors have a stronger impact on Virtual Coupling performance. To deal with this issue, this work exploits the ability of Deep Reinforcement Learning based strategies in defining an optimal control policy via an iterative exploration of the surrounding unknown environment and without detailed knowledge of the plant dynamics. Specifically, we propose a novel Deep Deterministic Policy Gradient based control strategy to coordinate and manage the High-Speed Trains convoy such that this latter can autonomously adapt its behaviour to all the encountered driving scenarios. The effectiveness of the proposed approach is evaluated via simulation analyses, carried-out via an ad-hoc implemented Virtual Coupling Train System simulation platform. After verifying the efficiency of the training process in ensuring the fulfilment of the Virtual Coupling control objectives, extensive non-trivial simulations, also involving cooperative manoeuvres, are performed for the validation phase. Results confirm how the proposed model-free Deep Deterministic Policy Gradient approach guarantees the Virtual Coupling for nonlinear heterogeneous High-Speed Train convoys despite the co-presence of uncertainties and unknown external factors. Finally, the advantages and the benefits of the proposed data-driven control are disclosed via a comparison analysis against model-based control strategies. [ABSTRACT FROM AUTHOR]

—Currently, most vehicles are generally equipped with roll stability control system or electronic stability control system to improve stability. However, when encountering emergency obstacle avoidance and similar conditions, roll stability control system may compete with path tracking control system for vehicle control, resulting in the inability to balance path tracking and roll stability. Therefore, a closed-loop feedback Nash game collaborative control method is proposed to solve the collaborative problem between the two control systems. Firstly, a fifth-order vehicle model with coupled yaw-roll dynamics is presented, which was extended to a vehicle-road closed-loop model based on lateral position, yaw angle and road preview information. Secondly, the path tracking control system and roll stability control system are regarded as two agents in the dynamic game control process. On this basis, a Nash game collaborative control strategy is designed by fully considering the control interaction between two game agents. Finally, considering the influence of uncertain disturbances, a finite-time minimax robust control strategy is proposed by using minimax optimization theory. Simulation and hardware in loop experiments show that the minimax robust regulator based on Nash game controller can effectively improve the path tracking and roll stability performance of vehicles. Moreover, the regulator improves the robustness of the system when it is subjected to bounded uncertain lateral disturbances. [ABSTRACT FROM AUTHOR]

The new railway mobility paradigm Virtual Coupling, recognized as one of the most promising solutions to face the ever-increasing demand in railway transportation and the saturation of network capacity, enables two or more trains to virtually couple in a single convoy, hence reducing the headway among them. Within this context, the design of an effective and robust Virtual Coupling control strategy for uncertain nonlinear heterogeneous train convoys, able to simultaneously cope with uncertain nonlinearities and unexpected/unpredictable external factors, is an open challenge in the railway field. This is very crucial for High-Speed Trains, where, due to the high-speed operating ranges, uncertain factors have a stronger impact on Virtual Coupling performance. To deal with this issue, this work exploits the ability of Deep Reinforcement Learning based strategies in defining an optimal control policy via an iterative exploration of the surrounding unknown environment and without detailed knowledge of the plant dynamics. Specifically, we propose a novel Deep Deterministic Policy Gradient based control strategy to coordinate and manage the High-Speed Trains convoy such that this latter can autonomously adapt its behaviour to all the encountered driving scenarios. The effectiveness of the proposed approach is evaluated via simulation analyses, carried-out via an ad-hoc implemented Virtual Coupling Train System simulation platform. After verifying the efficiency of the training process in ensuring the fulfilment of the Virtual Coupling control objectives, extensive non-trivial simulations, also involving cooperative manoeuvres, are performed for the validation phase. Results confirm how the proposed model-free Deep Deterministic Policy Gradient approach guarantees the Virtual Coupling for nonlinear heterogeneous High-Speed Train convoys despite the co-presence of uncertainties and unknown external factors. Finally, the advantages and the benefits of the proposed data-driven control are disclosed via a comparison analysis against model-based control strategies. [ABSTRACT FROM AUTHOR]

Utilizing parallel learning technology and an event-triggering mechanism, we introduce an adaptive security tracking control approach for nonlinear systems with both matched and mismatched uncertainties. The methodology commences with an overview of the constraints imposed by the control barrier function (CBF) on the system state, followed by the selection of a suitable CBF. An augmented system is constructed by amalgamating the system state and tracking error, with the mismatched uncertainty being decomposed to introduce an auxiliary system. Incorporating the CBF into the performance metrics ensures that the system state remains within a secure region. Subsequently, the paper employs an event-triggering mechanism to derive an event-based secure Hamiltonian–Jacobi–Bellman (HJB) equation. An adaptive single-critic network, designed using parallel learning technology, approximates the solution to the event-based secure HJB equation. Lastly, the Lyapunov method is employed to demonstrate the uniform ultimate boundedness (UUB) of both the tracking error and weight error. The efficacy of the proposed method is validated through two nonlinear examples. [ABSTRACT FROM AUTHOR]

Surge is a form of dynamic instability created as an unstable pattern in the flow of fluid and can severely affect centrifugal compressor performance by causing fluctuations in flow and pressure parameters. Due to the heavy and costly damage that the surge may cause in various industrial processes such as petrochemical plants, it is necessary to design an appropriate control system to reduce the effect of this phenomenon. The problem of active surge control of a centrifugal compressor using the throttle control valve (TCV) in the presence of compressor parametric uncertainties as well as large demands on upstream and downstream loads is investigated in this work. The control objective was to design a robust control system that can stabilize the compressor over a wide operating range without knowing the upper bound for the uncertainties and load demand. The controller should also react quickly by generating a smooth control signal without saturating the control input. These objectives are achieved by designing a sliding mode controller along with a nonlinear disturbance observer. The performance of the proposed disturbance observer-based controller is evaluated under various operational and load conditions and the results are compared against fuzzy type 1, conventional sliding mode, and wavelet-based neural network robust adaptive controllers. The results show that the proposed method can tolerate large disturbances without any knowledge on the upper bound of the incident disturbance, both on the downstream pressure and upstream mass flow which is highly desirable in practice. The comparative study proves the efficacy of the proposed method using various performance measures. The study also confirms the superior robust performance and stability of the proposed method in front of matched and mismatched disturbances as well as model uncertainties especially close to the instability boundary. Although choosing a TCV actuator has made the control system design easier, the sensitivity of the control valve to flow coefficient and zero calibration under different operating ranges of the compression system is studied carefully and some recommendations for the users are provided. • Active surge control of a compressor in the presence of uncertainty as well as the external disturbances is investigated. • A disturbance observer-based sliding mode controller is proposed to stabilise the compressor system in the surge area. • The nonlinear feedforward disturbance observer is designed to estimate the abrupt changes taking place in the system. • The proposed disturbance observer-based technique is compared with other techniques under various operational conditions. • The robust performance and stability of the method especially close to the instability boundary is proven numerically. [ABSTRACT FROM AUTHOR]

This paper proposes a tube model predictive control method considering uncertainties of renewable energy generation in the low-voltage distribution network. For relatively low dependence on communication networks, a decentralized voltage control framework is urgently needed to be developed for voltage regulation in the low-voltage distribution network. Opposed to the traditional voltage control techniques, a novel decentralized tube model predictive voltage control (TMPC) strategy is proposed. First, this strategy entails the formulation of a discrete model encompassing distributed photovoltaic units and energy storage systems intertwined with the distribution grid model based on voltage sensitivity. Then, considering the worst case of voltage deviations caused by uncertain and stochastic power fluctuation, we specifically discuss a robust positively invariant to determine the control section of controllers. Further, the strategy employs tube model predictive controllers encompassing nominal and auxiliary controllers in distribution areas. The nominal controller generates a central path for different voltage operating points of each distribution area, and the auxiliary controller makes all trajectories lie in a bounded neighborhood called a tube. The effectiveness of the proposed control strategy is investigated on a test system containing renewable energy resources. • A novel decentralized control structure is proposed to serve voltage control for distribution networks, which can cooperate for accurate voltage control with random and fluctuant renewable energy. • In the nominal controller, operation points of DGs are generated considering the generation and load scheduling. In the auxiliary controller, detailed control objectives and constraints are proposed for suppressing disturbances of DGs. • To balance the conservation and performance, a worst-case-based robust positively invariant is developed to quantify the range of tubes to cope with the randomness. [ABSTRACT FROM AUTHOR]

Distributed energy resources (DER) are integrated into a microgrid through dc-dc power electronic converters. The bidirectional dc-dc converter regulates charging and discharging operations of ESS. Model predictive control (MPC), is a high-performance control technique for these converters, but it is limited in robustness to parameter mismatch, model uncertainties and sensor measurement noise. Therefore, in this paper, an improved hybrid cascade-parallel extended state observer (CP-ESO) is proposed, for model-free predictive control, to guarantee both robustness to parameter/model uncertainties and measurement noise suppression. A novel structurally-adaptive ESO scheme is also proposed to improve the disturbance rejection of CP-ESO during transient response. These results are supported by analysis and design guidelines for the selection of optimal sub-frequencies. Experimental results, for a bidirectional dc-dc boost converter, validate the effectiveness of the proposed methods against model uncertainties, external disturbances from variable input voltage and load, as well as measurement noise. • Analysis and design guidelines for multi-frequency extended state observers (ESO). • Improved cascade-parallel extended state observer with better noise suppression. • Novel structurally-adaptive ESO that gives better transient disturbance rejection. • Experimental validation with a bidirectional dc-dc boost power converter. [ABSTRACT FROM AUTHOR]

Linear control-oriented models are important to represent canal dynamics for designing controllers. This study focuses on hydraulic control structure (gate) modelling to address the complex interdependent behavior inherent in irrigation canals. A comprehensive mathematical model that incorporates the water level with gate-opening to model discharge is introduced for single and multiple canal pool scenarios. The proposed model captures the hydraulic coupling within and among canal pools, a key finding. The model is evaluated extensively under uniform and non-uniform flows across three distinct canals, highlighting the model's applicability to various systems. The uncertainty inherent within the nominal model is also assessed for varying operating conditions and hydraulic parameters. The proposed model is compared with the existing and the Saint-Venant (SV) model, showing improved accuracy in water-level predictions. This advancement in hydraulic modelling contributes to adaptable canal models essential in developing robust controllers to enhance water management in irrigation canals. • A mathematical canal model is developed incorporating water level in hydraulic control structure. • A generalised model structure applicable to an arbitrary number of pools is developed. • The proposed model outperforms existing models in estimating water levels by capturing hydraulic coupling. • The model is evaluated across diverse canal configurations under uniform and non-uniform (backwater) flow conditions. • The model's uncertainty is assessed for varying operational conditions and the roughness coefficient. [ABSTRACT FROM AUTHOR]

We present a novel artificial intelligence approach that encompasses both predictive and prescriptive aspects for the challenging task of model-based control of industrial wood planers. These sophisticated lumber finishing machines are known for the complexity of their operation, and the available data pertaining to the planing process exhibits complex, non-linear patterns. First, we leverage an ensemble of Gaussian Processes with a specialized weighting scheme named Automatic State Matching , achieving a 39% reduction in prediction error for the thickness of the outgoing board compared to conventional industry methods, as corroborated by real-world data. Subsequently, the predictive strategy is utilized in a novel robust control strategy which exploits the properties of Gaussian Processes to prescribe settings for wood planers. An empirical evaluation on simulated data demonstrated the viability of our prescriptive method, resulting in an 83% reduction in deviation from a predetermined target dimension. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for the synthesis of multiple resonant controllers in the voltage regulation loop of uninterruptible power supplies (UPSs) operating in parallel with droop control. The resonant controller gains are calculated through a convex optimization problem aiming to attenuate the rms value of circulating current between the UPSs. Linear matrix inequalities (LMIs) constraints ensure the robust closed-loop robust stability and performance under the insertion or removal of UPSs and load variations. Experimental results from two 3.5 kVA UPSs illustrate the advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper introduces theoretical conditions for the computation of a novel type of state-feedback controller that makes use of Linear Parameter Varying approaches for synthesis. The novelty of this new State-Feedback controller lies on the fact that the controller has a fixed structure with constants matrix gains. However, the controller gains are affine on a parameter dependent basis function, which allows the controller to self-schedule according to real-time changes of the varying parameters. This type of controller is conceived with a focus on implementation, as in contrast with most other LPV approaches. The implementation of this Parameter-Dependent State-Feedback controller does not require any online interpolation or matrix inverse operations, independently of the number of varying parameters. The performance of the proposed approach is validated in a Scaled Autonomous Vehicle for steering control in a path tracking application. [ABSTRACT FROM AUTHOR]

One of the biggest challenges in optimizing the shape of complex solids is the requirement to maintain a reasonable mesh quality not only at the boundary but also for the bulk discretization of the interior. Thus, additional regularization and, in many cases, re-meshing of the structure during the iterative process is unavoidable with a Lagrangian description. By tracking the shape update using an Eulerian representation, embedded boundary methods are a promising technique for eliminating mesh distortion problems. This work consistently combines the unique features of implicit Vertex-Morphing and embedded boundary methods, facilitating the node-based shape optimization of solids with industrial complexity. One of the crucial elements for solving the primal problem on a fixed background grid is an efficient and robust quadrature scheme. To this end, we incorporate the open-source C++ framework QuESo (https://github.com/manuelmessmer/QuESo) developed for the numerical integration of arbitrarily complex embedded solids defined by oriented boundary meshes, e.g., in STereoLithography (STL) format. Meanwhile, applying the Helmholtz/Sobolev-based (implicit) filter to the vertices of the embedded boundary mesh not only exploits the extensive design space of node-based optimization but also ensures robust control over the feature size. To realize the above methodology, this work introduces a novel sensitivity analysis that yields mesh-independent shape gradients with respect to the immersed boundary. Through a specific sensitivity weighting, we recover a continuous gradient field from discrete values calculated at the nodes of the background grid. In addition, the presented workflow ensures robust enforcement of challenging geometrical constraints, including minimum wall thicknesses and design space limitations. We critically assess our approach with benchmarks and structures of industrial relevance. In all examples, trivariate B-Spline bases span the background grid, providing highly accurate finite element solutions and shape sensitivities at every iteration. Moreover, the elimination of mesh distortion problems enables a successful termination at the local optimum, even for large shape modifications. • Extension of Vertex-Morphing to embedded boundary methods. • Rigorous elimination of mesh distortion problems. • Discretization-independent sensitivity analysis. • Robust enforcement of design space constraints. • Application to solid structures with industrial complexity. [ABSTRACT FROM AUTHOR]

With the widespread application of unmanned aerial vehicles, harsh environments require higher control performance. Numerous existing works offer solutions for handling external disturbances during flight; however, the timeliness of the disturbance compensation is rarely discussed. This study focuses on trajectory tracking under external wind disturbances, specifically under two types of interference: average wind and wind shear. After compensating for the disturbance, a novel antidisturbance sliding mode control is designed based on reference model, to realize accurate, robust, and chatterless trajectory tracking under wind disturbance. Firstly, we addressed the limitations of conventional extended state observers, nonderived forms, and inadequate use of information by introducing state compensation function observers to enhance estimation accuracy for states and disturbances that are challenging to measure directly. Moreover, the disturbance variation is estimated using tracking differentiator and then compensated in the controller to enhance antidisturbance sensitivity. In addition, the effectiveness and stability of the proposed observer and controller are analyzed. Finally, a two-step verification is presented, including simulation with input disturbances and actual flight under two wind field types; multiple industrial fans are used to generate the average wind and wind shear during the experiment. Two robust control methods, state-of-the-art active disturbance rejection control and sliding mode control, are also implemented for comparison, and the results indicate that more than 61.2% accuracy improvement over comparison methods is achieved in simulation and actual experiments. [ABSTRACT FROM AUTHOR]

This study presents a novel approach for controlling an industrial process that exhibits uncertainty and significant nonlinear features. The proposed method utilizes a virtual unmodeled dynamic and data-driven nonlinear robust predictive control strategy. The representation of a controlled object involves a composite state space model that combines both linear and high-order nonlinear elements. Moreover, a robust model predictive controller is developed using the linear component. In addition, the notion of one-step optimal feedforward is used in combination with a compensating controller to handle the high-order nonlinear factor specifically. Subsequently, a compensation controller with incremental characteristics is developed for a modified version of the high-order nonlinear term. Furthermore, the stability conditions of the closed-loop system are derived, and an analysis is conducted on the stability and convergence of the proposed approach. The TTS20 three-capacity water tank was utilized in both simulations and practical scenarios. The study demonstrated that the suggested approach successfully reduces system output variations and enhances overall performance in response to unpredictable changes in the process's dynamic features. • Adding a feed-forward branch to the control system raises the stability margin, which is better than the RMPC. • This study explores the integration of unmodeled dynamics using a real-time predictive compensation technique. • The effective use of implicit data has the potential to enhance the control system's ability to adapt and adjust itself. [ABSTRACT FROM AUTHOR]

This paper presents the effect of a Battery Energy Storage System (BESS) on the power system inter-area oscillations under changing load conditions. The dynamic interaction between the BESS control modes and synchronous generators, along with BESS control parameters, influence the damping of prominent inter-area oscillations under different loading conditions. Furthermore, H ∞ mixed sensitivity scheme-based Wide-Area Damping Controller (WADC) is proposed for BESS. This controller is designed using the Linear Matrix Inequality (LMI) framework to mitigate the prominent inter-area oscillation of the power system. Sensitivity to control parameter variation and the geometric measure of the observability are utilized to select the location and feedback signal for the WADC. The performance of the proposed WADC is compared with an Energy Storage System-based stabilizer and WADC proposed in an existing work on a modified New England ten-machine benchmark system. The Real-Time Digital Simulator (RTDS) platform is used to assess the real-time viability of the proposed WADC. The simulation results demonstrate that the proposed WADC can effectively diminish several inter-area modes. Additionally, it offers robust performance under varying load conditions, contingencies and with communication delays in feedback signals. The proposed controller is also effective under the system integrated with Doubly Fed Induction Generator-based Wind Turbine System. • The impact of BESS on the power system inter-area oscillation damping is investigated. • The impact of dynamic control mode interaction between SGs and BESS on the system oscillation modes under various operating conditions is investigated. • A H ∞ mixed sensitivity scheme-based WADC is designed for BESS to alleviate the power system inter-area oscillations. • The H ∞ mixed sensitivity scheme-based WADC is implemented in the RTDS to assess its feasibility in a real-time environment. [ABSTRACT FROM AUTHOR]