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This paper proposes a systematic approach for optimizing the distribution of local models in multi-model control systems (MMCS) to enhance overall robustness. While existing literature discusses this method for linear parameter varying (LPV) and uncertain linear time-invariant (LTI) systems, significant limitations persist in addressing nonlinear dynamic systems. Robust control tools like the gap metric and generalized stability margin (GSM) have limited effectiveness in analyzing the robustness of nonlinear feedback systems. To address these challenges, novel concepts of the gap metric and GSM are introduced to determine central operating points (COPs) within local operating areas (LOAs) across the total operating area (TOA). These COPs guide the extraction of affine disturbance local models (ADLMs). Additionally, an optimization problem based on the s-gap metric and GSM is presented to optimize COPs placement and LOAs boundaries. Challenges such as non-monotonic behavior of the cost function and complexity arising from the s-gap metric formulation necessitate novel solution methods. To address these, constraints are applied to the cost function, and a novel discrete optimization approach is introduced. Finally, theoretical findings are applied to the Duffing system, pH neutralization process, and continuous stirred tank reactor (CSTR) plant to evaluate the proposed method's effectiveness. This comprehensive validation across different systems underscores the versatility and practical utility of the proposed approach. • We provide a systematic solution for addressing multi-model control systems (MMCS) for nonlinear dynamic systems. • Our approach stands out for its versatility, extending its applicability to a broad spectrum of nonlinear dynamical systems. • The solution is achieved through the utilization of s-gap metric concepts. • We tackle the optimization problem in a discrete form, introducing a novel clustering-based optimization approach. • The non-monotonic behavior of the s-gap metric is addressed by incorporating constraints into the problem formulation. [ABSTRACT FROM AUTHOR]

In this paper, for macro–micro composite motion platform with piezoelectric hysteresis, an finite-time adaptive robust control method based on extended hysteresis observer is proposed. The dynamic model of macro–micro system is constructed at first. An extended hysteresis observer was designed to estimate the actual displacement and speed of motion system. Then, an adaptive robust control law is designed to eliminate the uncertain hysteresis model parameters. After this, exponential convergence result of the proposed control method is given and proved. By setting the expected bandwidth of macro–micro system, the gain adjustment process of the control method can be reduced in computation. The effectiveness of the proposed control method is demonstrated by comparison with other control methods in simulation, and the proposed control method has more stable tracking effect and smaller tracking error. • Finite-time adaptive robust controller for Macro–micro composite platform. • Design and implementation of extended state observer for piezoelectric hysteresis. • Design of gain adjustment process to simplify calculation. [ABSTRACT FROM AUTHOR]

This article proposes a preview-based robust path-tracking control technique for maintaining lateral stability and tracking performance of autonomous vehicles, particularly in the presence of external disturbances and modeling uncertainties. First, a vehicle-road dynamic model with tire norm-bounded uncertainty is developed, which includes time-varying velocities and preview distances. The lateral and yaw dynamic characteristics are also analyzed in the frequency domain. Subsequently, an optimal preview model corresponding to sideslip-yaw rate states and longitudinal velocities is formulated employing a fuzzy logic model, and the sideslip angle is estimated using a sliding mode observer. Furthermore, a linear parameter-varying (LPV)/ H ∞ path-tracking controller that satisfies the pole placement and performance constraint is constructed to guarantee robustness and lateral stability across the whole parameters space with the coexistence of external disturbances and parametric uncertainties. Finally, the simulation results demonstrate that the proposed controller substantially enhances tracking performance while also maintaining excellent lateral stability. • A vehicle-road dynamic model with norm-bounded uncertainty for path-tracking controller design is built and analyzed. • An optimal-preview model is innovatively produced by utilizing velocity and the sideslip-yaw rate state of the vehicle. • An LPV/ H ∞ path-tracking control structure integrated optimal-preview model is proposed to improve tracking performance. [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]

Uncertainty can lead to jitter or overshoot in mechanical systems, necessitating the design of multiple constraints to stabilize them. This paper proposes a control structure based on the generalized Udwadia–Kalaba equation to address these constraints simultaneously. An uncertain dynamical model is developed, incorporating both equality and inequality constraints. By integrating diffeomorphism theory, a robust control strategy is designed to ensure compliance with these constraints. Utilizing the Lyapunov approach, the uniform boundedness and uniform ultimate boundedness of the dynamical system are demonstrated. Finally, the feasibility of the proposed control method is validated through its application to a belt conveyor system. • Equality constraints and inequality constraints are simultaneously considered in dynamical system based on the generalized Udwadia–Kalaba approach. • A robust control for handling inequality constraints that does not affect equality constraints is designed. • The robust control can render the uncertain system uniformly bounded and uniformly ultimately bounded. • The method is proposed of applying inequality constraints to belt conveyors to avoid belt breakage and folding faults in engineering. [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]

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]

This article presents a robust finite control set predictive scheme for a stand-alone squirrel cage induction generator (SCIG) drive. This technique is considered an alternative to the drive system due to the inclusion of system nonlinearities and fast dynamic response. The control objective in the distributed generation environment is to fix the output voltage to follow the stand-alone requirement. The strategy establishes optimized switching instants for cost function minimization for both source and load converter control and diminished cross-coupling amid active and reactive power during transient scenarios. The scheme is designed to achieve the minimal effect caused by the parameter uncertainties. During source and load changes, this work will also address the maintenance of dc-link voltage, machine, and load variables at the set value, supported by machine and load-end converter control to achieve stand-alone load objectives. In addition, the presented scheme is also tested with random variation of speed to check the efficacy of the control configuration. The drive performance is evaluated by simulation using MATLAB/Simulink environment. Comprehensive real-time findings obtained from a scaled laboratory test bench using dSPACE-1104 are provided to verify the feasibility of the predictive solution. • Distinct design approach of predictive control for SCIG based drive system feeding stand-alone load. • The developed generator side converter strategy controls the active power flow from the SCIG by regulating the dc-link voltage. • The performance of the control scheme is found to be much superior under load transients, and input power variation. • The uncertainty in the values of the machine parameters is also tested and system offer better dynamic performance. • Demonstration of MATLAB Simulation and, then validation with Real-Time results. [ABSTRACT FROM AUTHOR]

Denial of services (DoS) attacks exist in wind integrated power system. DoS attacks can cause network-induced delay and packages loss in information transmission. Meanwhile, considering the parameter perturbation of controller and system model uncertainty in wind integrated power system, these may cause the system dynamic performances degradation or even instability. Based on the above considerations, the joint non-fragile automatic generation robust control of wind integrated power system under DoS attacks is studied in this paper. In order to ensure the expected system performance and more effectively utilize the limited network communication resources under DoS attacks, a novel dynamic multi-event driven mechanism based joint non-fragile H ∞ automatic generation control method is proposed. By constructing a suitable Lyapunov-Krasovskii functional and utilizing the Shur complement lemma to handle nonlinear matrix inequality, the sufficient conditions are derived to guarantee the asymptotic stability of wind integrated power system under DoS attacks. Furthermore, the performance of the proposed non-fragile regulator is demonstrated through a four-area wind integrated power system to show the feasibility and applicability. The analysis result indicates that the proposed scheme provides stronger robustness, higher wind energy utilization efficiency and more efficient communication mechanism. [Display omitted] • A multi-event driven mechanism (MEDM) based joint non-fragile control scheme is derived. • The wind-integrated power system model based on MEDM is established. • The MEDM is integrated into the joint non-fragile controller design under DoS attacks. • The MEDM based joint non-fragile H ∞ automatic generation control strategy is proposed. • It provides stronger robustness and higher wind energy utilization efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes a tube-based model predictive control strategy for linear systems with bounded disturbances and input delay to ensure input-to-state stability. Firstly, the actual disturbed system is decomposed into a nominal system without disturbances and an error system. For the nominal system, solving an optimization problem, where the delayed control input is set as an optimization variable, yields a nominal control law that enables the nominal state signal to approach to zero. Then, for the error system, the Razumikhin approach is used to identify a robust control invariant set. Using the set invariance theorem, an ancillary control law is developed to confine the error state signal in the invariant set. Combining the two results, we obtain a control law that enables the state signal to remain within a robustly invariant tube. Finally, the effectiveness of the developed control strategy is validated by simulations. • An ancillary control is used to ensure the state errors stay in the invariant set. • A constraint on the delayed input is added to ensure feasibility of the algorithm. • By introducing a state error term, a novel Lyapunov function is proposed. [ABSTRACT FROM AUTHOR]

Childhood adversity (CA) has a substantial correlation with mental health problems. Keeping a healthy lifestyle is essential for mental health interventions; it is unclear, however, how healthy lifestyle affect the relationship between CA and persistent mental health problems. This longitudinal study (n = 1112, 54.5 % male) collected the data on CA (measured through three dimensions: threat, deprivation and unpredictability), mental health problems, and lifestyle factors. Group-based multi-trajectory modeling (GBMTM) was utilized to estimate trajectories for three mental health problems (i.e., depression, ADHD and overanxiety). Close friendships, regular physical activity, appropriate sleep duration, shorter screen time, and healthy eating were combined to establish a healthy lifestyle score (which ranges from 0 to 5). Higher scores indicated a healthier lifestyle. Three trajectories of mental health problems were identified: persistently low risk (24.9 %), persistently medium-high risk (50.0 %), and persistently high risk (25.1 %). Multinomial logistic regression showed that high adversity (high-threat: β = 2.01, P < 0.001; high-deprivation: β = 1.03, P < 0.001; high-unpredictability: β = 0.83, P = 0.001; high-overall adversity: β = 1.64, P < 0.001) resulted in a persistently high risk of mental health problems; these outcomes were maintained after robust control for covariates. Further lifestyle stratification, null associations were observed among children with a healthy lifestyle, irrespective of their gender; however, after controlling for covariates, the above associations remained relatively stable only among boys. The generalizability of our findings is restricted by 1) limited racial diversity and 2) missing data. This finding underscores the benefits of promoting a healthy lifestyle in children to prevent persistent mental health problems caused by CA. • We identified three trajectories of multiple mental health problems in children. • Children exposed to high adversity are more likely to be at persistently high risk for mental problems. • A healthy lifestyle can help buffer the risk of a persistently high risk of mental health problems caused by adversity [ABSTRACT FROM AUTHOR]

[Display omitted] • The construction of unmanned lunar bases requires the work of lunar-based equipment. • This study proposes a robust control algorithm for the stable movement of lunar based equipment. • The proposed robust control strategy performs well in real-time experiment. • The proposed robust control algorithm has advantages over existing control strategies. In lunar exploration, lunar-based equipment assumes the responsibility of mobility and transportation during the construction of unmanned lunar base. Legged robots are an important form of the lunar-based equipment due to their mobility and terrain adaptability. However, the influence of lunar terrain and lunar soil cannot be ignored when it comes to studying the mobile stability of lunar-based equipment. Utilizing the dynamic model of the robotic leg, this study proposes a new robust control algorithm, MBC (Model-Based with Continuous expression) algorithm, for lunar-based equipment's robotic leg, and its effectiveness is established through experimentation and theoretical validation with the Lyapunov second method. In the design and verification, the contact force of lunar soil and the lunar environment with low gravity are considered, indicating the applicability of the proposed MBC method in special lunar scenarios. Compared to the conventional PD (Proportional-Differential) and MPD (Model-Based Proportional-Differential) techniques, MBC robust algorithm ultimately demonstrates superior stability and rapidity with a smaller steady state error. [ABSTRACT FROM AUTHOR]

In previous studies, structure vibration control mainly focused on integer-order systems or commensurate fractional-order (FO) dynamics systems. In this paper, we propose an adaptive radial basis function (RBF) neural network feedback (ARBF-FK) controller for FO building structure vibration systems with viscoelastic (VE) dampers, uncertain structure parameters and unknown seismic waves. Firstly, use a FO multi-order state space description for FO building structural vibration systems. Then, the design of the ideal feedback controller is based on the stability theory of FO multi-order systems. Moreover, to reduce the cost and facilitate the practical implementation of the control, unknown earthquake seismic waves is approximated by a RBF neural network, the ARBF-FK controller is proposed. In addition, to guarantee the stability of the closed-loop control system and avoid falling into local optimum, network weights are adapted by the FO Lyapunov stability theory instead of gradient descent algorithms. Finally, the convergence rate of the system is analyzed and perform various tests on the ARBF-FK controller. The simulation results demonstrate that the ARBF-FK controller has superior performance and is very robust to control FO building structure vibration systems with uncertain structure parameters and unknown external earthquake excitation. • A FO multi-order state space description method of FO building vibration systems is constructed. • An online adaptive ARBF-FK robust control strategy for FO building vibration systems is proposed. • Adaptive weights of neural networks are derived using the FO Lyapunov theory. [ABSTRACT FROM AUTHOR]

In this paper, the problem of highly performance motion control of tank bidirectional stabilizer with dead zone nonlinearity and uncertain nonlinearity is addressed. First, the electromechanical coupling dynamics model of bidirectional stabilizer is developed finely. Second, the dead zone nonlinearity in bidirectional stabilizer is characterized as the combination of an uncertain time-varying gain and a bounded disturbance term. Meanwhile, an adaptive robust controller with dead zone compensation is proposed by organically combining adaptive technique and extended state observer (ESO) through backstepping method. The adaptive technique is employed to reduce the impact of unknown system parameter and dead zone parameter. Furthermore, the ESO is constructed to compensate the lumped uncertainties including unmodeled dynamics and dead zone residual, and integrated together via a feedforward cancellation technique. Moreover, the adaptive robust control law is derived to ensure final global stability. In stability analysis, the asymptotic tracking performance of the proposed controller can be guaranteed as the uncertainty nonlinearities in tank bidirectional stabilizer are constant. It is also guaranteed to achieve bounded tracking performance when time-varying uncertainties exist. Extensive co-simulation and experimental results verify the superiority of the proposed strategy. • A mechatronic dynamics model of the tank bidirectional stabilizer is developed, which is accurately modeled including couplings, nonlinearities and uncertainties. • The parametric adaptive function is constructed to update the unmeasurable dead zone parameters online, and the extended state observation technique is introduced to eliminate the dead zone nonlinearity and unmodeled dynamics. • The Lyapunov stability analysis demonstrates that the asymptotic tracking capability is guaranteed when the system uncertainty is constant, and the uniformly bounded tracking performance is guaranteed owing to the existence of time-varying uncertainties. • Comparative analysis of co-simulation and experiment confirms the effectiveness and feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The aim of the present article is to design a robust fractional-order (FO) finite-time (FnT) control able to tackle Hölder disturbances of second-order nonlinear systems. First, a novel sliding manifold with Arc-Tangent function is suggested for second nonlinear systems. It has been proven that the system states globally converge to the origin in FnT using the proposed sliding mode variable. To ensure a FnT stability of the sliding variable, a robust control is developed. By using fractional operators, a uniformly continuous control law is designed to tackle Hölder disturbances. Furthermore, the suggested approach is shown to be resistant to matched Hölder disturbances and uncertainties that are continuous but not necessarily differentiable. Moreover, the FnT stability of quadrotors using the proposed control, that is our second result. The quadrotor simulations analysis demonstrates the practicality of the proposed FnT controller in the presence of Hölder disturbances. • A simple nonlinear manifold design is proposed to ensure a finite-time convergence of quadrotors unlike the existing nonlinear sliding variables (Mousavi et al., 2021). • Hölder disturbances are addressed using fractional switching control law in the design of the proposed control scheme. • Compared to existing rejection disturbances (Ju et al., 2022; Labbadi and Cherkaoui, 2020; Razzaghian, 2022; Mousavi et al., 2021), the proposed FOFTC scheme has a faster convergence speed. [ABSTRACT FROM AUTHOR]

This paper proposes a novel controller design using adaptation based modified super twisting control to facilitate trajectory tracking and hovering maneuvers for the quadrotor. The controller gains of the existing modified super twisting control require bounds on the disturbance for trajectory tracking and hovering of the quadrotor. In this paper, the controller gains are adapted using the proposed dynamic adaptation law without knowing the actual disturbance or their upper bounds. The controller is designed within a nonlinear framework without performing linearization of quadrotor dynamics, which enables the proposed controller to remain effective even when the states deviate significantly from their nominal values. The performance of trajectory tracking and hovering of the quadrotor in the presence of disturbance is demonstrated using numerical simulations. In order to assess the effectiveness of the controller, the performance of the adaptation based modified super twisting control is compared to the existing modified super twisting control, and the proposed controller outperforms the existing one. • Adaptive modified super twisting control for robust trajectory tracking and hovering. • Dynamic adaptation law relaxes the need for an upper bound on disturbance. • Numerical simulations show the validity of the proposed approach. • Performance is compared with the existing modified super twisting control. • Efficacy is demonstrated with Dryden wind and sinusoidal disturbances. [ABSTRACT FROM AUTHOR]

This paper presents a novel methodology that combines fractional-order control theory with robust control under a parametric uncertainty approach to enhance the performance of linear time-invariant uncertain systems with integer or fractional order, referred to as Fractional-Order Robust Control (FORC). In contrast to traditional approaches, the proposed methodology introduces a novel formulation of inequalities-based design, thus expanding the potential for discovering improved solutions through linear programming optimization. As a result, fractional order controllers are designed to guarantee desired transient and steady-state performance in a closed-loop system. To enable the digital implementation of the designed controller, an impulse response invariant discretization of fractional-order differentiators (IRID-FOD) is employed to approximate the fractional-order controllers to an integer-order transfer function. Additionally, Hankel's reduction order method is applied, thus making it suitable for hardware deployment. Experimental tests carried out in a thermal system and the assessment results, based on time-domain responses and robustness analysis supported by performance indices and set value analysis in a thermal system test-bed, demonstrate the improved and robust performance of the proposed FORC methodology compared to classical robust control under parametric uncertainty. • New method for fractional controllers using Interval poles, improving performance. • Sets region to sweep frequency based on settling time and stability region of α. • Reduces conservativeness, allowing stability changes for flexible performance. • Ensures target with chosen fractional-order controller based on desired actions. [ABSTRACT FROM AUTHOR]

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]

• 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]

This study presents a novel hybrid control strategy for single-link flexible-joint robot manipulators, addressing inherent uncertainties and nonlinear dynamics. By integrating nonlinear reduced-order active disturbance rejection control (NRADRC) with backstepping control, the proposed method effectively estimates and mitigates nonlinear dynamics and external disturbances. Utilizing a nonlinear reduced-order extended state observer (NRESO) enhances resilience to internal and external uncertainties. The global stability of the proposed controller is rigorously established using the Lyapunov approach. Numerical comparisons with state-of-the-art nonlinear control methods demonstrate the superior efficiency and robustness of the proposed approach, especially under varying payloads and disturbances, advancing robotic control solutions. • Proposes a robust high-efficiency controller for single-link flexible-joint manipulators. • Innovates by integrating backstepping and Active Disturbance Rejection Control. • Features a reduced-order observer independent of the system's mathematical model. • Ensures global asymptotic stability with Lyapunov recursive methods. [ABSTRACT FROM AUTHOR]

The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand for enhanced precision, extended range, and increased load-bearing capacity in objective motion carrier (OMC). To address this challenge, this study introduces an innovative OMC that employs a ball screw mechanism as its primary driving component. Furthermore, a robust nonlinear motion control strategy has been developed, which integrates fast nonsingular terminal sliding mode, experimental estimation techniques, and adaptive radial basis neural network, to mitigate the impact of nonlinear friction within the ball screw mechanism on motion precision. The stability of the closed-loop control system has been rigorously demonstrated through Lyapunov theory. Compared with other enhanced sliding mode control strategies, the maximum error and root mean square error of this controller are improved by 33% and 34% respectively. The implementation of the novel OMC has enabled the establishment of a high-resolution bio-optical microscope, which has proven its effectiveness in the microscopic imaging of retinal organoids. • Novel SMC Strategy: To address the limitations of traditional SMC, characterized by high gains and pronounced chattering, a novel SMC strategy is introduced. • Online Estimation and Compensation: The utilization of TDE techniques enables online estimation and real-time compensation of unknown terms. • Biophotonic Microscope Development: The research culminates in the development of a biophotonic microscope, wherein the objective motion carrier plays a crucial role in achieving focal plane movement. [ABSTRACT FROM AUTHOR]

This paper presents a two-loop control framework for robotic manipulator systems subject to state constraints and input saturation, which effectively integrates planning and control strategies. Namely, a stability controller is designed in the inner loop to address uncertainties and nonlinearities; an optimization-based generator is constructed in the outer loop to ensure that state and input constraints are obeyed while concurrently minimizing the convergence time. Furthermore, to dramatically the computational burden, the optimization-based generator in the outer loop is switched to a direct model-based generator when the tracking errors are sufficiently small. In this way, both a high tracking accuracy and fast dynamic response are obtained for constrained robotic manipulator systems with considerably lower computational burden. The superiority and effectiveness of the proposed structure are illustrated through comparative simulations and experiments. • A general and systematic constrained control scheme for robotic manipulators. • Nonlinearities, uncertainties, state and input constraints are considered. • Adaptive robust controller is designed for high tracking accuracy. • Optimization-based generator is designed for fast dynamic response. • Experiments on Franka robotic manipulator reveal the effectiveness. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization problem with a fixed-time approach for a flexible spacecraft subject to vibrations of flexible modes, unknown bounded disturbance, and inherent uncertainty. To estimate the modal variables of a flexible spacecraft which are often unmeasurable in practice, an observer with guaranteed fixed-time convergence is designed. Using the estimated modal variables, a fixed-time non-singular sliding mode controller is designed so that the desired attitude can be reached before a pre-specified time threshold regardless of the spacecraft's initial attitude. By incorporating the estimated modal variables in the control design, significant reduction in the steady-state error of the system response is achieved. The proposed control system is further enhanced with an adaptive law to increase robustness against unknown external disturbances and uncertainties. Stability analysis based on Lyapunov theory guarantees the convergence of observer estimation error and spacecraft attitude error to a pre-determined set before a fixed threshold. Simulation results validate the promising performance of the proposed control system, highlighting its effectiveness in achieving accurate and robust attitude control for flexible spacecraft. • A fixed-time observer with guaranteed convergence is designed. • A fixed-time non-singular sliding mode controller is developed to guide the spacecraft's attitude towards a desired target. • To further enhance the robustness of the control system, an adaptive law is integrated into the proposed controller. • The stability of the closed-loop system is rigorously analyzed using Lyapunov theory. [ABSTRACT FROM AUTHOR]

In this study, a linear quadratic integral differential game approach is applied to regulate and track the Euler angles for a quadrotor experimental platform using two players. One produces commands for each channel of the quadrotor and another generates the worst disturbance based on the mini-maximization of a quadratic criterion with integral action. For this purpose, first, the attitude dynamics of the platform are modeled and its parameters are identified based on the Nonlinear Least Squares Trust-Region Reflective method. The performance of the proposed controller is evaluated for regulation and tracking problems. The ability of the controller is also examined in the disturbance rejection. Moreover, the influence of uncertainty modeling is studied on the obtained results. Then, the performance of the proposed controller is compared with the classic Proportional Integral Derivative, Linear Quadratic Regulator, and Linear Quadratic Integral Regulator. The results demonstrate the effectiveness of the Game Theory on the Linear Quadratic Regulator approach when the input disturbance occurs. [Display omitted] • Implementation of a linear quadratic controller based on differential game theory. • Introducing an action integral to the controller to eliminate steady-state errors. • Proof of optimality of the proposed controller. • Evaluation of the controller's performance on a quadrotor experimental setup. • Comparison of the controller's performance with other robust control methods. [ABSTRACT FROM AUTHOR]

Assessments of action semantics consistently reveal markers of Parkinson's disease (PD). However, neurophysiological signatures of the domain remain under-examined in this population, especially under conditions that allow patients to process stimuli without stringent time constraints. Here we assessed event-related potentials and time-frequency modulations in healthy individuals (HPs) and PD patients during a delayed-response semantic judgment task involving related and unrelated action-picture pairs. Both groups had shorter response times for related than for unrelated trials, but they exhibited discrepant electrophysiological patterns. HPs presented significantly greater N400 amplitudes as well as theta enhancement and mu desynchronization for unrelated relative to related trials. Conversely, N400 and theta modulations were abolished in the patients, who further exhibited a contralateralized cluster in the mu range. None of these patterns were associated with the participants' cognitive status. Our results suggest that PD involves multidimensional neurophysiological disruptions during action-concept processing, even under task conditions that elicit canonical behavioral effects. New constraints thus emerge for translational neurocognitive models of the disease. • We examined EEG markers of action concept relatedness in Parkinson's disease (PD). • Patients and controls were faster to process related than unrelated action trials. • Underlying N400 and theta effects were robust in controls and absent in patients. • Accompanying mu rhythms were contralateralized in patients. • Key neural signatures of action relatedness and grounding are altered in PD. [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]

The widespread use of wheeled mobile robots (WMRs) in many fields has created new challenges. A critical issue is wheel slip, which, if not accurately determined and controlled, causes instability and deviation from the robot's path. In this paper, an intelligent approach for estimating the longitudinal and lateral slip of wheels is proposed that can effectively compensate for the negative effects of slippage. The proposed algorithm relies on three regression networks to estimate the longitudinal slip ratio of the right and left wheels and sideslip angle on terrains with different friction coefficients. The datasets collected during tests on different surfaces with various maneuvers are used to train the artificial neural networks (ANNs). A developed dynamic model of a WMR considering wheel slip and modified traction force is presented. The adaptive robust controller, based on sliding mode control (SMC), is introduced to deal with the problems related to slipping, unknown uncertainties, and disturbances. The simulation results demonstrate that the presented controller has better performance than SMC in handling external disturbances and uncertainties, which leads to reduction in tracking error and faster convergence to zero. The proposed controller with an intelligent slip estimator, has been applied to a four-wheel mobile robot to demonstrate its effectiveness and feasibility. The high accuracy of slip estimation in the mentioned intelligent algorithm has resulted in the presented method being on average 26% more effective in reducing the tracking error than the control method without slip compensation in each test for circular trajectory. • Developing a dynamic model of WMR using modified traction force. • Proposing slip estimator based on an intelligent learning for both longitudinal and lateral slip. • Eliminating the time delay in slip estimation and compensating for its effect in the same time step by predicting the slip amount. • Improved robot performance in trajectory tracking on slippery surfaces. [ABSTRACT FROM AUTHOR]

To address the trajectory tracking issue of upper-limb rehabilitation exoskeleton with uncertainties and external disturbances, this paper proposes a fractional-order ultra-local model -based model-free finite-time robust controller (FO-FTRC) using predefined performance sliding surface. Different from previous model-free control strategies, a novel multi-input multi-output (MIMO) fractional-order ultra-local model which is a virtual model is proposed to approximate the complex uncertain nonlinear exoskeleton dynamics in a short sliding time window. This allows the design of controller to be independent of any exoskeleton model information and reduces the difficulty of controller design. The developed robust model-free control method incorporates a fractional-order quasi-time delay estimator (FO-QTDE), unknown disturbance estimator (UDE) as well as prescribed performance sliding mode control (PPSMC). The FO-QTDE is utilized to estimate the unknown lumped uncertainties which employs short time delayed knowledge only about the control input. However, the low-pass filter is always added for FO-QTDE when disturbances change fast, which leads to unavoidable estimation error. Then, UDE is designed to further eliminate the estimation error of FO-QTDE to enhance control performance. The PPSMC is constructed to converge sliding surface to zero in a finite time. Besides, the sliding surface is always limited in performance boundaries. After that, the overall system stability and convergence analyses are demonstrated by using the Lyapunov theorem. Finally, with the comparison to other methods of α -variable adaptive model free control (α -AMFC), time-delay estimation-based continuous nonsingular fast terminal sliding mode controller (TDE-CNFTSMC), time delay estimation (TDE)-based model-free fractional-order nonsingular fast terminal sliding mode control (MFF-TSM) and fractional-order proportion–differential (PD β), the co-simulation results on 7-degree-of-freedom (DOF) iReHave upper-limb exoskeleton virtual prototype and experiment results on 2-DOF upper-limb exoskeleton are obtained to illustrate the effectiveness and superiority of the proposed FO-FTRC method. • A fractional-order ULM is proposed to approximate complex exoskeleton to achieve MFC. • A QTDE and disturbance estimator is designed to eliminate the lumped uncertainties. • The paper achieves the FT stabilization under fractional-order ULM design framework. • The co-simulation experiments on 7-DOF iReHave exoskeleton and experiment on 2-DOF. [ABSTRACT FROM AUTHOR]

The issues faced by hybrid electric vehicles (HEVs) include locating and managing free energy to preserve resource dynamics and constraints while preserving prolonged autonomy. This study assessed a hybrid electric vehicle (HEV) equipped with a fuel cell (FC), battery, direct current generators (DCGs), and supercapacitor (SC) to meet the power needs of an automobile utilizing variable power converters. This study examines four HEV energy management strategies (EMSs), increasing clean environmental power penetration by utilizing the HEV's kinetic energy, as a new contribution. Strategies for Proportional-Integral (PI), State-Machine (SM), Artificial Neural Network (ANN), and Adaptive Neural Fuzzy Inference System (ANFIS) EMSs are discussed. In addition to implementing direct torque control with a space vector modulation-based ANFIS controller (ANFIS-DTC-SVM), this study proposes to insert DCGs in the front wheels of HEVs for free energy production. Simulations of EMSs yielded approximative findings, achieving a 22.2 (%) free-exploited kinetic energy. The ANN-based EMS surpassed the competition, yielding the highest energy efficiency 98.2 (%) and the lowest fuel consumption 48.68 (SI). As a result of maximizing battery utilization and limiting fuel consumption, the examined HEV's dependability and stability were confirmed and reached, highlighting the importance of kinetic energy. [Display omitted] • Creation of new energy without pollution. • The exploitation of EV's kinetic energy to produce the power.‎ • Applying different energy management strategies.‎ • Configuration and control of the two-wheel-drive electric vehicle.‎ • Improvement of energy efficiency and fuel consumption. [ABSTRACT FROM AUTHOR]

For most nanopositioning systems, maximizing positioning bandwidth to accurately track periodic and aperiodic reference signals is the primary performance goal. Closed-loop control schemes are employed to overcome the inherent performance limitations such as mechanical resonance, hysteresis and creep. Most reported control schemes are integer-order and combine both damping and tracking actions. In this work, fractional-order controllers from the positive position feedback family namely: the Fractional-Order Integral Resonant Control (FOIRC), the Fractional-Order Positive Position Feedback (FOPPF) controller, the Fractional-Order Positive Velocity and Position Feedback (FOPVPF) controller and the Fractional-Order Positive, Acceleration, Velocity and Position Feedback (FOPAVPF) controller are designed and analysed. Compared with their classical integer-order implementation, the fractional-order damping and tracking controllers furnish additional design (tuning) parameters, facilitating superior closed-loop bandwidth and tracking accuracy. Detailed simulated experiments are performed on recorded frequency-response data to validate the efficacy, stability and robustness of the proposed control schemes. The results show that the fractional-order versions deliver the best overall performance. • Fractional-order control improves nanopositioning systems, enhancing bandwidth and accuracy. • These controllers offer more parameters, boosting achievable bandwidth and accuracy. • Simulations confirm efficacy, stability, and robustness, even with unmodelled effects. • Achievable bandwidth increases by up to 17%, accuracy improves by 35%. • Fractional-order control allows for significant improvements in nanopositioning systems. [ABSTRACT FROM AUTHOR]

Path-tracking and lane-keeping tasks are critical to guarantee safety and navigation performance considerations for deploying autonomous cars. This paper presents a novel control framework for the path-tracking control of high-speed autonomous cars with structured uncertainties. This study introduces a nonlinear adaptive control system based on a fractional-order terminal sliding mode system while incorporating a novel Gaussian Nonsingleton type-3 fuzzy system (FOTSM-NT3FS). Therefore, the proposed controller is independent of the information about the ego vehicle's dynamic information, and instead, the dynamics are approximated through a developed NT3FLS. The developed control system exhibits robustness to measurement errors and faulty sensors, because the inputs to the NT3FS are uncertain. In order to guarantee the boundedness of the adaptation parameters, the σ − mod approach is employed. The Lyapunov stability theorem and Barbalat's lemma are used to ensure the uniform ultimate boundedness of the closed loop system and the convergence of tracking errors to the origin in finite time. High-fidelity co-simulations with CarSim and MATLAB are performed to verify the effectiveness of the proposed control scheme and are also compared to other reported methods in the literature. Based on the obtained results, the schemed controller exhibits competitive effectiveness in path-tracking tasks and strong efficiency under various road conditions, parametric uncertainties, and unknown disturbances. • Robust path tracking for uncertain-input cars, ensuring reliability despite errors. • Adaptive control with fuzzy integration for high-speed autonomy, precise maneuvering. • Stable navigation using Gaussian Nonsingleton type-3 fuzzy system, smooth tracking. • Efficient path tracking under uncertainties, outperforming existing methods. [ABSTRACT FROM AUTHOR]

The uncertainty in mobile robot greatly affects control accuracy. This makes it difficult to apply to more rigorous high-precision engineering fields. Therefore, the fuzzy set theory is introduced to describe the uncertainty. Based on that, the fuzzy mobile robot system is established. The virtual speed controller using backstepping method is designed. Then, a robust control method is proposed to guarantee the uniform boundedness and uniform ultimate boundedness of the controlled system. Furthermore, the balance optimization problem of the performance and cost of the controlled system is explored. By minimizing the performance index containing fuzzy numbers, the optimal control parameter is obtained. Compared with the linear quadratic regulator algorithm, which is the representative optimal robust controller, the proposed control method and optimization strategy based on fuzzy set theory are verified to be effective. The control accuracy is further improved. • The kinematic and dynamic models of the mobile robot are established. • A virtual speed controller is designed by using the backstepping method. • A deterministic robust control is proposed to ensure the system performance. • A fuzzy performance index is introduced for optimizing parameter. [ABSTRACT FROM AUTHOR]

To address the escalating demand and supply constraints for semiconductor devices, manufacturing techniques such as thermal atomic layer etching (ALE) have been utilized, which require robust temperature control systems. Radiative heating with lamps is a promising method for achieving fast and precise temperature control. However, there is limited research in analyzing the dynamic control of radiative lamp heating systems. In this study, a transient, two-dimensional (2-D) radiative heating model in a cross-flow thermal ALE reactor is constructed through Ansys Fluent. A sparse identification (SINDy) modeling approach is applied to build a reduced-order dynamic model for the prediction of system states in the control system. A model predictive controller (MPC) is then developed to bring the wafer surface temperature to the target temperature while preserving the uniformity of the temperature on the wafer surface. Control is implemented by adjusting the powers of three groups of heating lamps independently. Notably, a novel feedback-based time-varying steady-state penalty approach is applied with the MPC in this study, which enables the system to reach the target temperature range within 10 s while maintaining temperature uniformity for 1000 s. • Computational fluid dynamics modeling of wafer temperature profile. • Sparse model identification using spatio-temporal temperature data. • Model predictive control using nonlinear sparse model. • Implementation of MPC on CFD model of the process. [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]

A novel robust controller is designed for Electric Helicopter Tail Deceleration (EHTD) system which is subject to uncertainties and nonlinearity. Then, the optimal parameters of the control are solved based on Stackelberg game theory. The fuzzy set theory is used to describe the uncertainty bound, which is distinguished from probability theory or fuzzy logic theory. Based on two-player (leader and follower) Stackelberg game, two performance indexes are proposed for novel robust controller which contains two optimal parameters. The system performance and control cost are included in performance indexes. Then, based on Stackelberg strategy, the optimal decisions are made by leader and follower, which can minimize the performance indexes. Therefore, by numerical simulation, the EHTD system is applied to prove that the design of robust control and optimal parameters based Stackelberg strategy are effective. • A novel robust controller is designed for Electric Helicopter Tail Deceleration system which is subject to uncertainties. • The novel robust controller contains two adjustable control parameters. • Based on Stackelberg game theory, the optimal decision can be chosen by players (leader and follower). [ABSTRACT FROM AUTHOR]

An air–ground heterogeneous unmanned swarm system coordination is considered. The system consists of N unmanned aerial vehicles (UAVs) and one unmanned ground vehicle (UGV). This forms a complicated mission, which consists of the following four different tasks. First, the aerial vehicles are in a compact formation, while avoiding collision with each other. Second, the aerial vehicles should stay close to the ground, while avoiding collision with the ground. Third, the aerial vehicles should stay close to the ground vehicle. Fourth, the ground vehicle should follow a desired trajectory. These tasks reflect two seemingly contradictory nature: close to (due to tracking) and away from (due to avoidance). The effective control design should address all four tasks even in the presence of uncertainty. By two creative transformations, this multitude of tasks are consolidated in a χ -measure. An adaptive robust control, which includes a robust control scheme and an online adaptation law, is then proposed to render guarantee boundedness performance of this χ -measure. As a result, the control design is able to accomplish the combined tracking-avoidance mission for the uncertain swarm system. Despite the presence of conflicting aspects between these tasks, the designed controller exhibits outstanding performance. • A multitasking control framework is proposed for air-ground coordinated systems. • Two contradictory tasks of tracking and avoidance are solved by one control method. • An adaptive robust control is designed for the systems with uncertainty. • Multiple performances of the systems are realized by one controller. [ABSTRACT FROM AUTHOR]

Successive approximation techniques are effective approaches to solve the Hamilton–Jacobi–Bellman (HJB)/Hamilton–Jacobi–Isaacs (HJI) equations in nonlinear H 2 and H ∞ optimal control problems (OCPs), but residual errors in the solving process may destroy its convergence property, and related numerical methods also pose computational burden and difficulties. In this paper, the HJB/HJI partial differential equations (PDEs) for infinite-horizon nonlinear H 2 and H ∞ OCPs are handled in a unified formulation, and a sparse successive approximation method is proposed. Taking advantage of successive approximation techniques, the nonlinear HJB/HJI PDEs are transformed into sequences of easily solvable linear PDEs, to which the solutions can be computed point-wise by handling simple initial value problems. Extra constraints are also incorporated in the solving process to guarantee the convergence under residual errors. The sparse grid based collocation points and basis functions are then employed to enable efficient numerical implementation. The performance of the proposed method is also numerically demonstrated in simulations. • The proposed method handles nonlinear H 2 and H ∞ problems with a unified formulation. • Residual errors are explicitly considered in the designed numerical scheme. • The scale of the resultant quadratic programming problem only grows polynomially. [ABSTRACT FROM AUTHOR]

This paper proposes a method for high-performance motion control of the dual-valve hydraulic system subject to parameter and model uncertainties, unknown proportional valve dead-zone, and servo valve fault. By constructing a detailed dual-valve fault system model (DFSM), a disturbance observer-based adaptive robust fault-tolerant controller is proposed via the backstepping method. This controller integrates a model-based fault detection algorithm for real-time fault monitoring and subsequent controller reconfiguration. Additionally, the DFSM-based adaptive robust control (ARC) technique is applied to handle the unknown dead-zone problem and other nonlinearities, ensuring precise control. Once the servo valve fault occurs, a nonlinear observer estimates the fault and collaborates with the ARC to establish a reconfigured controller, thereby maintaining motion control. The effectiveness of the proposed method has been experimentally verified. • The novel fault-tolerant control algorithm for dual-valve hydraulic system is investigated. • The novel dual-valve faults system model is proposed. • The model-based fault detection algorithm and nonlinear disturbance observer are established. • The advanced adaptive robust fault-tolerant controller is designed. [ABSTRACT FROM AUTHOR]

Mechanical systems subject to constraints play a essential role in the field of control engineering, profoundly influencing the design and performance of control strategies. Consequently, there is a compelling need to explore diverse control methods to effectively tackle the complex task of stabilizing nonlinear systems while ensuring the constraints are not violated. In this context, this paper proposes a design procedure for position-constrained controllers in robot manipulators. The solution relies on the construction of a diffeomorphism (a differentiable coordinate transformation) that maps all the trajectories of the constrained dynamics into an unconstrained one. The controller design is carried out in the unconstrained dynamics without dealing directly with the constraints. The proposed family of controllers employ an explicit control law which circumvents the need for additional time-consuming computation for feasibility and/or optimization. Moreover, the proposed controller is parametrized by a class of diffeomorphisms which can be selected by the designer. Exponential stability in constrained and unconstrained position states is achieved, in the certain case. For the uncertain case, the controller is augmented through sliding modes guaranteeing finite-time convergence towards the manifold and keeping the exponential convergence within the manifold dynamics. The approach is validated through experiments in an actual 2 DOF lightweight robot manipulator. • A diffeomorphism-based control law for MIMO constrained nonlinear systems. • The explicit controller ensures (local) exponential convergence of the all states. • A robustification of the controller to deal with uncertainties via sliding modes. [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]

Wheeled mobile robots (WMRs) have a wide range of applications in logistics transportation and industrial productions, among which the motion control has always been one of the hot spots in the current WMR researches. However, most of previous designed controllers assumed that the WMR motion had no slippage. Ignoring the slippage factors usually results in a decrease in control performance and even leads to unstable motion. To address such a challenge, a kinematic model with differential flatness is established through dynamic feedback-linearization, which comprehensively considers the multidirectional slippage of mobile robot, including longitudinal and steering slippage. Subsequently, benefited from the one-to-one mapping of states and inputs to flat outputs in differential flat system, an adaptive robust control (ARC) method is proposed to stabilize the system. Different from previous robust control studies, even if the knowledge of the upper bound of system uncertainties is unknown in advance, the proposed adaptive robust controller can still achieve satisfying performance by adaptive estimation of the upper bound of system uncertainties. The effectiveness and feasibility of the proposed method are confirmed by comparative experiments on WMR with slippage disturbance. [ABSTRACT FROM AUTHOR]

This paper proposes a fixed-time tracking control for robot manipulators in the presence of parametric uncertainties and disturbances. An auxiliary function is first proposed for constructing a fixed-time sliding manifold. Benefited from this fixed-time sliding manifold, a singularity-free robust control is proposed to evade the effects of algebraic loop problem of the commonly-used sliding mode controls (SMC). The key advantages of the proposed approach are: (i) exact fixed-time stability featuring the convergence time does not relate to the initial conditions and is acquired in advance; (ii) the singularity and algebraic loop problems are eliminated completely; (iii) a simple and intuitive control structure is used for easy implementation of trajectory tracking control for uncertain robot manipulators with faster transient and higher steady-state precision. Simulations and experimental comparisons validate the improved tracking performance of the proposed approach. • Propose a non-singular terminal sliding mode control with fixed-time convergence. • Prove exact fixed-time tracking stability. • Features include exact fixed-time stability with simple structure. • Demonstrate the improved performance. [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]

Due to the underactuated and unstable nature, the control of unmanned bicycle robots is a challenge. The presence of unknown and time-varying uncertainties in the system adds to the difficulty of control for the unmanned bicycle robot. From the perspective of constraint-following, this paper proposes a new control approach to address uncertainties in the unmanned bicycle robot system. The uncertainties of the unmanned bicycle robot system are constrained within certain limits, but the bounds are unknown, which can pose a challenge for designing a control approach. Through the implementation of a leakage-type adaptive law that modifies the control system in accordance with tracking errors, the potential exists to confine the boundaries of uncertainties. The performance of uniform boundedness and uniform ultimate boundedness is shown by the Lyapunov stability theory. Numerical simulation of a representative case is performed to illustrate the effectiveness of the proposed control. • A controlled system is studied to follow a set of prescribed constraints. • Uncertainties are described as degree information based on fuzzy set theory. • An adaptive robust control is designed based on constraint-following. • Uniform boundedness and uniform ultimate boundedness can be guaranteed. • The proposed control is demonstrated by unmanned bicycle robot. [ABSTRACT FROM AUTHOR]