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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]

This paper describes a new approach to control stall and surge instabilities in the compressor system by using of finite time backstepping-based adaptive sliding mode method. The most important innovation of this study is to provide a finite time adaptive control method to simultaneously prevent the stall and surge instabilities in a compressor system in the presence of disturbance and uncertainty in the compressor characteristic curve as well as the throttle valve. The disturbance and uncertainty issues are covered by a robust sliding mode control and the gain coefficients of this controller as well as the estimation of uncertain terms are obtained by using the adaptive method. The Lyapunov stability criterion is used to evaluate the finite-time stability of the closed-loop system. The performance of the proposed method is compared with other literature methods through simulation in Matlab. The simulation results show that the proposed controller is better than the existing methods in terms of surge preventing and robustness against uncertainty and disturbance. [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]

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]

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]

Tilt rotor is a thrust force vectoring actuation strategy, mainly employed on aircraft to increase the control degrees of freedom. On multi-rotors, this strategy can be profitable for control purposes in terms of stability and maneuverability. Therefore, the present paper presents the design, model, and control of a 3 DOF tilt-rotor bi-copter test bench. The resulting apparatus is composed of a tilt-rotor bi-copter attached to an articulated arm that enables the vehicle to shift its position vertically, laterally, and rotate about its axis. Therefore, different control strategies for vehicles with tilting capability can be evaluated, ensuring safety and repeatability. In particular, the considered control task consists of tracking position references with proper enforcement of input constraints. For this purpose, a dual-mode control strategy, composed of a linear quadratic regulator and a model predictive controller, is adopted. Experimental results are compared to numerical simulations to corroborate the effectiveness and robustness of the proposed control system in the presence of model uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

This article presents a promising self-learning-based robust control for output voltage tracking in DC–DC buck power converters, particularly for applications demanding high precision performance in face of large load uncertainties. The design involves a computationally simple online single hidden layer neural network, to rapidly estimate the unanticipated load changes and exogenous disturbances over a wide range. The controller is designed within a backstepping framework and utilizes the learnt uncertainty from the neural network for subsequent compensation, to eventually ensure an asymptotic stability of the tracking error dynamics. The results obtained feature a significant improvement of dynamic and steady-state performance concurrently for both output voltage and inductor current in contrast to other competent control strategies lately proposed in the literature for similar applications. Extensive numerical simulations and experimentation on a developed laboratory prototype are carried out to justify the practical applicability and feasibility of the proposed controller. Experimental results substantiate the claims of fast dynamic performance in terms of 94% reduction in the settling time, besides an accurate steady-state tracking for both output voltage and inductor current. Moreover, the close resemblance between computational and experimental results is noteworthy and unveils the immense potential of the proposed control system for technology transfer. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of robust decentralized control of discrete-time nonlinear interconnected descriptor systems (IDS) under the influence of external disturbances. First, we utilize the Takagi–Sugeno fuzzy model (TSFM) to represent discrete-time nonlinear IDS. For controller design, a proportional-derivative (PD) feedback strategy is employed to formulate a decentralized fuzzy controller for the discrete-time Takagi–Sugeno IDS (DTTSIDS). Furthermore, robust and passivity constraints are incorporated into the controller design process to mitigate the effects of disturbances. Based on the Lyapunov function and free weight function methods, we can analyze the stability of the DTTSIDS. The proposed conditions are converted into Linear Matrix Inequality (LMI) conditions through Schur Complement technology so that we can solve the problem through MATLAB LMI-Toolbox. Finally, the effectiveness of the proposed methodology is demonstrated through three examples presented in the paper and a comparison with other existing studies is given in Example 3. [ABSTRACT FROM AUTHOR]

In this paper, the reference trajectory tracking issue of cooperative robots system with bounded uncertainty is investigated from a novel standpoint of servo constraint-following. The bound of uncertainty is not known but can be characterized by the fuzzy set theory. Then, establishes the dynamical model of cooperative robots system with fuzzy uncertainty. The process of the proposed controller design contains two steps. First, an adaptive robust control is investigated which can render the desired servo constraint to be followed even if there exists uncertainty in the system, and through stability analysis by selecting appropriate Lyapunov function which proves uniform boundedness and ultimate uniform boundedness of tracking error. The second step is to find a parameter selection guideline for the optimal control parameter. Based on the fuzzy description of system uncertainty, a performance index consisting of system performance and control cost can be developed. Then, the selection of optimal control parameters translates into finding the parameter that makes the performance index minimized. Finally, numerical simulations are performed on a two-planar two-link manipulator system for evaluating the performance of the proposed method. [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]

This paper presents a new robust control structure to control a 3-degree-of-freedom (3-DoF) helicopter in the presence of uncertainties, disturbance and actuators saturation. The 3-DoF helicopter is an underactuated system where only two DoFs can be fully controlled, so elevation and pitching motions are considered in this paper. Robust control methods conventionally generate control signals with high amplitude to suppress model uncertainties. Nonetheless, the practical actuators might not be able to supply such control efforts, causing actuator saturation. The actuator saturation phenomenon highly affects the motion control performance of the system and even can cause instability. To address this issue in this paper, firstly a smooth prevention function is utilized as an approximation of the practical actuator saturation, limiting the input torque/force in a prescribed range. However, to avoid violating the stability of the system by a prevention function, it should be considered in the dynamic model of the system, leading to a non-affine structure. Hence, the problem of controlling a non-affine system is addressed by proposing a new third-order dynamic model, as well as a robust control scheme. In this approach, a backstepping control is utilized, equipped with an adaptive radial basis function neural network to estimate and compensate for the adverse terms. Finally, the effectiveness of the proposed scheme is evaluated through a detailed simulation study on a 3-DoF helicopter. [ABSTRACT FROM AUTHOR]

This paper deals with the characterization of all stabilizing H ∞ controllers for plants described by any left coprime factors under an alternative framework, which is defined for both the continuous- and discrete-time cases. Moreover, we show that this framework can generate both continuous-time (strictly proper) and discrete-time (non-strictly proper) central controllers. In particular, the application will be carried out to track the trajectory of two-wheel non-holonomic mobile robots with differential drive used in robot soccer competitions in the Very Small Size (VSS) category. For simulation purposes, the structures of the discrete-time central controller and the continuous-time central controller applied to the same model of the robot under study will be presented. In addition, controller implementations will be presented, which will validate the effectiveness of the designed control systems against the references imposed on them. [ABSTRACT FROM AUTHOR]

Fuzzy set plays an important role in handling vagueness for controlling uncertain dynamical systems. However, conventional type-1 fuzzy set (T1FS) requires precisely defined membership function, which is usually unavailable in practical control applications. This study pioneers the use of IT2FS for the control design of uncertain dynamical systems to relax this limitation of conventional T1FS-based control design. Concretely, the considered (possibly fast) time-variant uncertainty is bounded with the bound lying within IT2FS (hence interval type-2 fuzzy dynamical system, IT2FDS). A robust control design approach is proposed without invoking any IF-THEN fuzzy rules, providing a two-layer performance. The lower layer renders uniform boundedness and uniform ultimate boundedness for the system by the Lyapunov analysis, ensuring the bottom line. The upper layer improves the fuzzy-based control performance by optimal gain design oriented by a two-player zero-sum game, taking advantage of the interval description of membership function. It is shown that the equilibrium of the game which contains the optimal gain always exists. A semi-analytical solution strategy for the equilibrium is given. This is the first endeavor in exploring IT2FS-based control design without using any IF-THEN rules. It is shown in the demonstrative examples that the proposed IT2FS-based approach can achieve better control performance than the conventional T1FS-based approach. [ABSTRACT FROM AUTHOR]

This article introduces a new fault-tolerant control method based on type-2 fuzzy systems with PID fast terminal sliding mode control. By integrating the advantages of proportional-integral-derivative (PID) control with fast terminal sliding mode (FTSM) control, a novel proportional-integral-derivative fast terminal sliding mode (PID-FTSM) is developed to accelerate convergence and decrease steady-state error. To provide outstanding fault tolerant control performance and approximation of system uncertainties, a type-2 fuzzy logical switching approach law eliminates the chattering phenomenon and reduce the need of prior knowledge without affecting the system's robustness. The overall stability of the system is verified using the Lyapunov function. Finally, several experiments demonstrate that the suggested technique outperforms alternatives. [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]

This paper presents an approach that combines Lyapunov theorem and particle swarm optimization (PSO). The combination tackles the optimization and stability concerns, in controlling permanent magnet synchronous motors (PMSMs). This approach ensures that the exploration is maintained within the search space region, enhances convergence properties, and reduces the risk of divergence or oscillations. This concept is utilized to optimize the field oriented controller (FOC) of PMSM using Matlab Simulink. Each proportional integral (PI) controller in the FOC system is individually optimized using the proposed technique. Simulation results confirm the effectiveness of the proposed method that gave a rise time of 0.71s, an overshoot of 0.04%, and a steady-state time of 0.725s as conjunction to traditional optimization methods. This provides more reliable and efficient frameworks, for solving complicated optimization problems. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate a wind power system utilizing a doubly fed induction generator (DFIG). In this configuration, the stator is directly connected to the grid, while the rotor is linked to the grid via a back-to-back converter. The primary aim is to develop a decoupled control system for the DFIG to improve power quality. To achieve this goal, we introduce a robust control technique as a means to control the reactive and active power of DFIG. This technique is known as sliding mode control. Furthermore, we propose a model-reference adaptive system estimator based on proportional and integral controllers (PI-MRAS) for sensor-less control of DFIG. This estimator is designed to accurately approximate the rotor resistance. The proposed control strategies enhance the performance of the wind energy conversion system, particularly considering variations in the machine's parameters. Simulation results demonstrate the high performance and robustness of control strategies. [ABSTRACT FROM AUTHOR]

The control of systems like: bipedal locomotion robots, space launch vehicle, offshore wind turbines, and active vibration control systems in buildings and bridges, have to ensure, besides stability and accuracy, the system's insensitivity to parameters' uncertainties, unmodeled dynamics, external disturbances, and measurements noise. In such systems analysis and controller design, a triple inverted pendulum can be used as a benchmark to mimic systems characteristics and effect of different sources of uncertainty. μ-synthesis is a robust control method which seeks a controller that minimizes the robust H-infinity performance of the closed-loop system through D-K iteration. The D-K iteration is not guaranteed to converge to a global, or even local minimum. Hence this paper proposes the enhancement of controller design by applying gazelle optimization technique to shape the fictitious output by determining the parameters of the performance weighting matrix. The incorporation of optimization with controller design allows avoiding getting unnecessarily conservative system at the expense of performance. The developed control system is simulated using Matlab R2023b for different scenarios of system uncertainty. The results show that the requirements of robustness and performance can be balanced through the right choice of cost function. The robust performance measure obtained is 0.6432 which leads to good response for both stabilization and tracking in the presence of uncertainty. The results also show that even the baseline μ-synthesis design achieves higher robust stability margin about 2.818, the proposed optimized method stabilizes the system with overshoot been reduced by 67.65% and steady state error reduced by 5.69% without sacrificing robustness. [ABSTRACT FROM AUTHOR]

Fuzzy reasoning gathered significant attention for its extensive utility since it was introduced. This work puts emphasis on its theoretical aspects and presents a framework for fuzzy logic reasoning considering time-varying uncertainty based on robust control theory. The proposed framework is built upon one basic setting, the Fundamental Axiom of Reasoning, which provides a criterion to demonstrate the validness of a chain reasoning by analytically quantifying its truth value based on multiple fuzzy implication models. The fuzzy reasoning system is casted to a dynamic system where the reasoning process is proactively controlled without violating the basic setting. The time-varying uncertainty in system variables or parameters is addressed by involving the delicately designed robust control. Furthermore, the diverse ways in which time-varying uncertainty impacts the system are also discussed, from modeling stage to control stage. Finally, an automated speed control problem with time-varying uncertainty is considered to demonstrate how to apply the proposed framework. [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]

Aiming at reducing the effect of time delay on the control performance of magnetorheological (MR) damper semi-active suspension, a control strategy with strong robustness to time delay is investigated in this study, including the force controller of MR damper, the robust controller and the predictive compensator. The force controller of MR damper is built based on the hyperbolic tangent function; the robust controller is built based on the simplified model of car body lateral vibration and is designed by μ-synthesis method considering the effect of time delay; then the Smith predictive model and the lateral velocity predictor are designed, which form the predictive compensator of semi-active controller to reduce the effect of time delay. To validate the effectiveness of the proposed control strategy, several conventional semi-active controllers are designed as comparative objects. The simulation results show that the proposed semi-active control strategy can maintain good performance when time delay is in the range of 0–100 ms and has better robustness to time delay compared with the conventional control strategy. [ABSTRACT FROM AUTHOR]

The principal contribution of this paper is the feedback design of an output trajectory tracking controller applied to a certain class of mechanical systems. The controller does not need velocity measurements for its implementation and achieves the trajectory tracking control aim. We propose adaptive estimators to determine the plant parameters and constant external perturbations. When the plant is affected by time-variant external perturbations, an observer filter that can be implemented to recover an estimation of the time-variant perturbations can replace the adaptive estimator. The closed-loop stability is analysed throughout Lyapunov tools. We illustrate the performance of the proposed control structure via numerical simulations and experiments, the numerical simulations are carried out for a pendulum coupled to a DC motor and the experiments are accomplished for a mass-spring-damper system. [ABSTRACT FROM AUTHOR]

In this study, a control system for a permanent magnet axial gap bearingless motor (AGBM) with a non-salient pole rotor is given using a non-linear disturbance observer-based robust control. In the proposed control strategy, low-pass filters are integrated into each virtual control input, and a powerful backstepping controller with integrated tracking error action is utilized. An integral backstepping control (IBSP) integrator is added to improve the system's robustness to parameter uncertainties and external disturbances. The low pass filter of dynamic surface control (DSC) based on an integral backstepping algorithm is adopted, from which the proposed control strategy improves steady-state accuracy and eliminates the derivative explosion phenomenon. Furthermore, non-linear lumped disturbance observers (NLDO) are used for axial displacement and rotation speed control loop to improve system stability by minimizing the impact of disturbances such as parameter uncertainties, unknown load torque and force, and unmodeled dynamics acting on the control system. Finally, the effectiveness, feasibility, and robustness of the proposed approach are demonstrated through simulation evaluation. The root means square deviation (RMSD) of axial displacement and angular velocity error are used to compare the presented techniques. [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 recent years, the wind conversion system (WCS) sector has witnessed a notable surge in the recognition of robust control methodologies. This paper undertakes a thorough investigation into a resilient control system customized for a self-contained WCS, seamlessly integrating a hybrid excitation synchronous generator (HESG) linked to an independent load during the crucial Maximum Power Point Tracking (MPPT) phase. The motivation for this study lies in the growing integration of HESG technology within WCS frameworks. Addressing a vital gap in prior research, which often focused on the structural intricacies of HESG while neglecting their operational efficacy, this work aims to rectify this imbalance. Traditional control systems have limitations for WCS applications. In particular, proportional-integral (PI) controllers struggle with power quality and system performance. In this context, our research presents a MATLAB-Simulink-based equivalent model of WCS that has been rigorously developed. A novel control strategy based on Backstepping Control (BSC) is proposed as a countermeasure to existing challenges. This method not only improves WCS control efficiency but also demonstrates its proficiency in optimizing MPPT. The simulations indicate that the suggested control system outperforms the PI system regarding power fluctuations, response time, overshoot, and durability. This result demonstrates its potential to improve the effectiveness of renewable energy production. [ABSTRACT FROM AUTHOR]

High-resolution range profile (HRRP) automatic recognition has been widely applied to military and civilian domains. Present HRRP recognition methods have difficulty extracting deep and global information about the HRRP sequence, which performs poorly in real scenes due to the ambient noise, variant targets, and limited data. Moreover,most existingmethods improve the recognition performance by stacking a large number of modules, but ignore the lightweight of methods, resulting in over-parameterization and complex computational effort, which will be challenging to meet the deployment and application on edge devices. To tackle the above problems, this paper proposes an HRRP sequence recognition method based on a lightweight Transformer named RLAT, which consists of rotary position encoding, local-aggregated attention unit (LAU), and lightweight feedforward neural network (LW-FFN). Rotary position encoding is utilized to embed the relative position information for the HRRP sequence. Local aggregation attention unit can effectively aggregate and extract local features by local group linear transformation, and then the self-attention mechanism is adopted for perception and enhancement of global information. Thereby, the enhanced features are extracted by lightweight FFN. In addition, this paper adopts Label Smoothing regularization to add noise to the sample labels, which can improve the generalization performance of themethod. Finally, the effectiveness of the proposed method in real scenes is verified based on the MSTAR dataset, a real-world dataset for radar target recognition. Experimental results show that the proposed method achieves superior recognition performance compared to other remarkable methods and achieves significant generalization performance and robustness under variant sample and limited sample conditions. RLAT achieved an accuracy of 99.86% on the MSTAR standard dataset and 99.73% on the MSTAR variant dataset. In particular, it achieves an accuracy of 95.83% with only 274 training samples. Furthermore, the proposed method is more lightweight, with 90.90% reduction in the number of parameters and 96.70% reduction in the computation compared to the Vanilla Transformer, which facilitates deployment in edge devices. [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]

This paper establishes a model-free finite-time tracking control of nonlinear robotic manipulator systems. The proposed controller incorporates both Time Delay Estimation (TDE) and an enhanced Terminal Sliding Mode Control (TSMC). The improved TSMC scheme is devised using Fractional-Order TSMC (FOTSMC) and Proportional-Integral-Derivative (PID) control to obtain robust tracking and high control performance. The TDE is designed to estimate the unknown nonlinear dynamics of robotic manipulators, including the Stribeck friction and the external disturbances. Due to Stribeck friction, the efiect of TDE error may fail to obtain the desired error performance; thus, another TDE loop is devised to compensate for TDE error generated by non-smooth frictions. The Lyapunov criterion is used to investigate the finite-time stability to analyze the behavior of the designed approach. Finally, computer simulations of the proposed method on PUMA 560 robotic manipulators are performed in contrast with FOTSMC and Adaptive Fractional-Order Nonsingular Terminal Sliding Mode Control (AFONTSMC). [ABSTRACT FROM AUTHOR]

In this paper, the adaptive robust H ∞ fault-tolerant control problem for a class of switched nonlinear systems with parameter uncertainty, disturbances and actuator failures is concerned based on event-triggered control strategy. The adaptive laws based on state-dependent switched strategy are designed to eliminate the effects of actuator faults and parameter uncertainties by using the estimations of the unknown upper bounds of uncertain parameters. Then, the robust H ∞ fault-tolerant technique and multiple Lyapunov functions method are used, the designed controller can guarantee that all signals of the switched closed-loop systems are uniformly bounded. Meanwhile, the desired H ∞ performance of the systems is promised. Finally, the simulation results are given to illustrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]