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The proton exchange membrane fuel cell (PEMFC) air supply system is a complex nonlinear system with strong coupling of air flow and pressure. To avoid oxygen starvation and unstable output performance during rapid load changes, the oxygen excess ratio (OER) and air pressure need to be controlled effectively. To cope with the nonlinearity, coupling and uncertainty of the PEMFC air system, this paper puts forward a coordinated controller regulating OER and air pressure based on the input-output linearization and sliding mode methods. Firstly, a control-oriented third-order model is proposed to describe the dynamic behavior of the air supply system. Secondly, this paper decouples the flow and pressure of the PEMFC air system by using an input-output linearization method to obtain two independent linear subsystems. Moreover, a sliding mode method, effectively coping with the uncertainty of the system model, is designed to regulate the OER and air pressure of the PEMFC, which enhances the robustness of the control system. The overall simulation outcomes show that the proposed controller regulates OER and cathode pressure with smaller root mean square error (RMSE) and mean absolute percentage error (MAPE) compared with the combined proportional integral (PI) and feedforward controller. • A modified model oriented to control of air supply system is proposed. • Input-output linearization and sliding mode are used to develop coordinated control strategies. • The outcomes illustrate that the air supply affects the output performance of the fuel cell. • Control performance in the presence of model uncertainty is verified. [ABSTRACT FROM AUTHOR]

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site. [ABSTRACT FROM AUTHOR]

Titanium-dioxide-grafted carbon paper (CP@TiO 2 ) has been synthesized by pyrolysis of tetrabutyl-titanate-treated filter paper, which is a simple, large-scale, and green method, while the product is a superior material for immobilising sulfur as a flexible free-standing electrode for lithium–sulfur (Li–S) batteries. The as-synthesised CP@TiO 2 membrane is constructed of interlaced circuitous carbon fibers and TiO 2 nanoparticles distributed on/in the void among the carbon fibers. The CP@TiO 2 –S membrane retains the robust and flexible structure of the CP membrane after infiltrating the sulfur, and the sulfur particles are homogeneously distributed within the CP@TiO 2 . As a free-standing cathode, the CP@TiO 2 –S membrane exhibits superior electrochemical performance than the CP-S membrane, displaying a reversible discharge capacity of 850 mAh g −1 after 200 cycles at 0.5C and a specific capacity of 660 mAh g −1 at 5C. The superior electrochemical performance of the CP@TiO 2 –S membrane is ascribed to the synergetic effect between the interlaced carbon fibers of the CP membrane, which provides electronic conduction pathways and works as mechanical support, and the TiO 2 nanoparticles with relatively high surface area and pore volume, which could physically/chemically trap polysulfides. The results indicate that the CP@TiO 2 membrane owns potential suitability for efficient, free-standing, and high-performance batteries. [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]

Today, hydrogen fuel cells (HFCs) have become very popular in various applications because of their ability to be a clean energy source. One of the difficulties associated with HFCs is their sluggish response to variations in the load. This paper presents a nested control strategy based on a type-2 neuro-fuzzy controller (T2NFC) to improve the HFC's dynamic response in a hybrid stand-alone power network using HFC and battery. A system model is constructed using Matlab-Simulink. An interleaved converter is used to draw the maximal power from the HFC and reduce the ripple in the HFC's current. Two T2NFCs control DC voltage and battery charge/discharge current. The robustness of the T2NFC is evaluated for input disturbance, output disturbance, and both disturbances. The results show that the proposed control strategy is robust against input and output disturbances. Also, it provides improved dynamic response of the HFC, lower ripple in HFC current, and less overshoot or undershoot in DC voltage both in transient and steady-state. For step reference input, the proposed controller improves settling time of 24.06 % and overshoot of 59.55 % compared to the conventional PI controller. The results verify the effectiveness of the proposed controller under different operating conditions of hybrid stand-alone power network with fuel cell and battery. • The response of HFC is enhanced, leading to faster and more accurate power generation. • The hydrogen fuel cell's current is experienced a significant reduction in ripples. • The hydrogen fuel cell is now being operated at its maximum power point. • A Type-2 Neuro-Fuzzy Controller is developed to provide robust control of the hydrogen fuel cell's output voltage. [ABSTRACT FROM AUTHOR]

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]

• We construct a multidimensional poverty index for chinese counties. • We establish a staggered DID model that controls for selection bias. • Highways significantly reduce county poverty. • The poverty-reduction effect of highways is conditional. • The poverty-reduction effect of highways diminishes with increasing altitude. This paper establishes a staggered difference-in-differences (DID) model to estimate the impact of highways on regional poverty using county-level panel data from China. We construct a multidimensional poverty index and use satellite-monitored night light brightness as a proxy indicator. The results demonstrate that highways significantly reduce county poverty and that the poverty reduction effect becomes increasingly pronounced over time. This result remains robust after controlling for non-random highway route selection. Furthermore, the poverty reduction effect of highways is conditional, with a significant poverty reduction effect in the less economically-developed western regions and non-municipal counties, and no significant poverty reduction effect in the economically-developed eastern and central regions and municipal districts. Moreover, the poverty reduction effect of highways gradually decreases as the average altitude of counties increases. Our tests provide empirical evidence for effective road investments in developing countries that incorporate poverty alleviation targets. [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]

The slant-axis telescope has a novel structure, and its unique structural design is more suitable for extreme environment such as the South Pole. However, there is a lack of research on the dynamic modeling and the controller design of slant-axis telescopes at home and abroad. This paper proposes a dynamic modeling and robust control method for slant-axis telescope. Firstly, the dynamical analysis of the slant-axis telescope is carried out. The 2-degree-of-freedom rigid body model of the telescope is established by the Lagrange method. Next, combining the flexibility of the driver system and disturbance, a mathematical model of the rigid-flexible coupling system of the slant-axis telescope is completed. Then, according to the established mathematical model, a sliding mode controller based on the disturbance observer is designed to suppress the disturbance, and realize the robust control of the slant-axis telescope. Finally, the simulation results show that the disturbance observer based sliding mode controller gets better dynamic performance and anti-disturbance characteristics than the traditional Proportion-Integration-Differentiation (PID) controller in the case of considering nonlinear external interference of the model. [ABSTRACT FROM AUTHOR]

Synchronization of memristive neural networks (MNNs) by using network control scheme has been widely and deeply studied. However, these researches are usually restricted to traditional continuous-time control methods for synchronization of the first-order MNNs. In this paper, we study the robust exponential synchronization of inertial memristive neural networks (IMNNs) with time-varying delays and parameter disturbance via event-triggered control (ETC) scheme. First, the delayed IMNNs with parameter disturbance are changed into first-order MNNs with parameter disturbance by constructing proper variable substitutions. Next, a kind of state feedback controller is designed to the response IMNN with parameter disturbance. Based on feedback controller, some ETC methods are provided to largely decrease the update times of controller. Then, some sufficient conditions are provided to realize robust exponential synchronization of delayed IMNNs with parameter disturbance via ETC scheme. Moreover, the Zeno behavior will not happen in all ETC conditions shown in this paper. Finally, numerical simulations are given to verify the advantages of the obtained results such as anti-interference performance and good reliability. [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]

This paper presents a gain-scheduling (GS) robust control strategy using the interpolation approach for ball screw drives while guaranteeing the system stability in the operating range. A set of linear-time-invariant (LTI) robust controllers is designed at selected table positions for the robustness against the uncertain load mass and the structural vibration suppression at those positions. By interpolating the LTI robust controllers, a GS robust controller is obtained to deal with the dynamic variations caused by the table motion. The closed-loop stability under the proposed GS robust controller is verified with the parameter-dependent Lyapunov function, which avoids tedious simulations to check the reliability of interpolating GS controllers before practical operations. The method presented in this paper enables the GS controller to consider the unmeasurable load mass in ball screw drives and simplifies the application complexity. The extensive experimental results demonstrate that the proposed GS robust controller significantly improves the tracking performance and the vibration suppression, in comparison to LTI controllers and GS controllers. • A gain-scheduling robust controller is developed for ball screw drives. • The table-position-dependent mode and the uncertain inertia are considered. • Parameter-dependent Lyapunov function is used to verify the closed-loop stability. • The proposed method improves the vibration suppression and trajectory tracking. [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]

In view of the weak energy supply stability of the single regional integrated energy system (RIES), the ability to deal with uncertainties is poor. To solve the problem of equilibrium optimization among system economy, robustness and efficiency, this paper interconnects multiple RIES with different resource to form multi-RIES through peer-to-peer energy trading. The control strategy of energy interactive operation involving multiple RIES is optimized. Using the uncertainty confidence set of renewable energy to depict the uncertainty on the source side, a two-stage distributed robust optimal control model for RIES based on data-driven is proposed, and the column and constraint generation (C&CG) algorithm is adopted to significantly improve the solution efficiency. Then, a multi-RIES cooperative game model with uncertain scenarios is proposed, and according to this model, a coupled C&CG-alternating direction multiplier method (ADMM) algorithm is proposed, which realizes the privacy protection of RIES and makes the system have good convergence performance. Finally, the case analysis proves that the strategy proposed in this paper can not only realize energy coordination and complementarity among multiple RIES, but also improve the stability of the system operation and significantly reduce the dependence of the system on the distribution network. • Data-driven RIES two-stage distributed robust optimization model is used to consider the uncertainty of renewable energy. • The multi-RIES cooperative game model based on data-driven two-stage distributed robust optimization is proposed. • A coupled C&CG-ADMM algorithm is proposed. [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 fuel cell airpath multivariable control problem of optimally coordinating the electric compressor motor and the back-pressure valve to achieve efficient and safe conditions, for both steady state and transient operation, has not been completely addressed in the literature. This paper proposes a nonlinear model predictive control strategy, implemented via the Garrett Motion proprietary NMPC toolbox, to regulate the oxygen stoichiometry and the cathode pressure of an automotive fuel cell airpath system, while avoiding compressor surge and air starvation. The controller set-points are optimized, using the nonlinear model, to achieve the maximum system power as a function of the operating stack condition. The effectiveness and robustness of the proposed control strategy have been validated by means of a simulated World harmonized Light-duty vehicles Test Cycle (WLTC), under both state feedback and model parameters uncertainties. [Display omitted] • MPC ensures compressor surge and oxygen starvation avoidance under severe dynamic scenarios. • Controller robustness assessed via a WLTC regulatory cycle under noisy and uncertain conditions. • Fuel efficiency is not significantly sensitive with respect to different controller calibrations. [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]

• 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]

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]

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]

• Hybrid microgrid is an emerging and exciting research field in power engineering. • Presents systematic review on various control strategies for hybrid microgrid. • Comparison between control strategies satisfying various control objectives. • Discussion on research challenges in use of effective and robust control scheme. • Discussion on emerging trends in hybrid microgrid's operation and control. Presently, there is huge development in conventional power systems due to the evolution of modern smart grids, wherein interconnected microgrids with a high level of energy storage and renewable energy penetration are gaining popularity in the modern distribution network. Future electrical distribution systems, or even transmission structures that combine AC and DC sources and loads are thought to be most promising when it comes to hybrid AC-DC systems. Using a combined operation of both AC and DC microgrids through an interfacing converter, hybrid AC-DC microgrids are advanced and benefitted with the use of both AC and DC topologies. Power management techniques for these microgrids are among the most important operational aspects. This paper provides a systematic review on numerous schemes to control hybrid AC-DC microgrids. Basically, microgrid control strategies are categorized as local control and coordinated control. Coordinated control is further divided in three control strategies as, distributed, centralized, and decentralized control. All these control strategies are employed to satisfy many control objectives, like bus voltage and frequency regulation, power sharing, and management, power quality, stability and reliability improvement, energy management, and economic dispatch. In this paper, various aspects associated with these control objectives and limitations in their control strategies are discussed. Also, future prospects on control of hybrid AC-DC microgrids and an effective and robust control strategy for power management possibly to be employed, are presented in the concluding section of this paper. [ABSTRACT FROM AUTHOR]

The paper develops a methodology for the design of coherent equalizing filters for quantum communication channels. Given a linear quantum system model of a quantum communication channel, the aim is to obtain another quantum system which, when coupled with the original system, mitigates degrading effects of the environment. The main result of the paper is a systematic equalizer synthesis algorithm which relies on methods of state–space robust control design via semidefinite programming. [ABSTRACT FROM AUTHOR]

This paper studies the adaptive neural networks (NNs) tracking control problem for a class of mobile robot systems with full-state constraints. First, to compensate for the adverse effects of the unknown dead-zone input, which is ubiquitous in mobile robot motors, a new robust control algorithm is put forward by the use of adaptive control technique. Then, a new unified barrier function (UBF) is constructed to deal with the problem of state constraints. Different from traditional barrier Lyapunov function (BLF) methods, which can only constrain the error of the system state and virtual controller, our proposed control method can constrain the system state directly by introducing a novel nonlinear transformation function and a new coordinate transformation. It's worth noting that the UBF can be utilized to deal with both constrained and unconstrained cases by resizing parameters without changing the control structure. Furthermore, adaptive NNs are introduced to approximate the uncertainty of the system. Finally, based on the Lyapunov stability theory, it is proved that all signals in the closed-loop system are ultimately bounded and the full-state constraints are never violated. The effectiveness of the control method is verified on simulation examples and a mobile robot experimental platform. [ABSTRACT FROM AUTHOR]

Under control action, wave energy devices typically display nonlinear hydrodynamic behaviour, making the design of energy maximising control somewhat onerous. One solution to approach the optimal performance for nonlinear control problem under model mismatches is to employ a linear control strategy, which can be robust to linear model mismatches. However, accurate characterisation of the uncertainty in the linear model is vital, if the controller is to adequately capture the full extent of the uncertainty, while not being overly conservative due to overestimation of the uncertainty. This paper describes a procedure, employing CFD-based numerical tank experiments, to accurately produce a nominal linear empirical transfer function model, along with an accurate estimate of the uncertainty bounds in that linear model, due to hydrodynamic uncertainty. A robust control case study is provided, illustrating the nominal model estimation process, and its corresponding uncertainty set, including the complete procedure, required to generate the robust controller. Robust control results, on the fully nonlinear CFD model, are provided to demonstrate the efficacy of the modelling and control philosophy. • Input signal synthesis and post-processing in numerical wave tank experiments. • Reducing conservatism in robust control of wave energy devices. • High-fidelity nominal and uncertainty model from computation fluid dynamics setup. • Quantifying hydrodynamic uncertainty description of the wave energy converters. • Empirical transfer function refinement based on physics of wave energy converters. [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]

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]

Minimizing the amount of fuel consumed by a moving vehicle can be formulated as an optimal control problem that determines the speed profile that the vehicle should follow. The fuel consumption is generally a function of speed and acceleration, and is optimized under external parameters (e.g., road grade or surrounding traffic conditions) known to affect fuel economy. Uncertainty in the traffic conditions, and in particular traffic speed, has seldom been investigated in this context, which may prevent the vehicle from following the optimal speed profile and consequently affect the fuel economy and the journey time. This paper describes two stochastic optimal speed control models for minimizing the fuel consumption of a vehicle traveling over a given stretch of road under a given time limit, where the maximum speed that can be achieved by the vehicle over the journey is assumed to be random and follow a certain probability distribution. The models include chance constraints that either (i) limit the probability that the desired vehicle speed exceeds the traffic speed, or (ii) bound the probability that the journey time limit is violated. The models are then extended into distributionally robust formulations to capture any uncertainties in the probability distribution of the traffic speed. Computational results are presented on the performance of the proposed models and to numerically assess the impact of traffic speed variability and journey duration on the desired speed trajectories: The results affirm that uncertainty in traffic speeds can significantly increase the amount of fuel consumption and the journey time of the speed profiles created by deterministic model. Such increase in journey duration can be mitigated by incorporating the stochasticity at the planning stage using the models described in this paper, and more so with the distributionally robust formulations particularly with higher levels of uncertainty. The solutions themselves generally exhibit low levels of speeds, which ensure the feasibility of the speed profile against any variabilities in the traffic speed. • Traffic speed uncertainty can increase fuel consumption and journey duration. • Stochastic optimal control helps to mitigate the impact of traffic speed uncertainty. • Distributionally robust optimal control can be used for larger uncertainties. • Stochastic optimal control models can be expressed as mixed integer programs. • Planned speeds tend to be lower to provide robustness against variability. [ABSTRACT FROM AUTHOR]