Actuator Saturation Research Articles

Asynchronous dissipative control of time-delay singular Markovian jump systems with actuator saturation

This paper focuses on the problem of asynchronous dissipative control for time-delay singular Markovian jump systems (SMJSs) with actuator saturation. In order to describe the asynchronous phenomenon between the system and the controller, a hidden Markov model (HMM) is adopted. In addition, the problem of actuator saturation is considered. Firstly, by the mode-dependent Lyapunov function, some novel sufficient criteria for guaranteeing the stochastic admissibility with dissipative performance of the system are proposed. Secondly, according to the derived criteria, a novel approach is established to design the controller gains. Thirdly, the domain of attraction of the system is given by the optimal method. Finally, two examples are given to verify the correctness of the proposed approach.

The positivity and event-triggered stabilization of Takagi-Sugeno fuzzy systems with actuator saturation

The positivity and event-triggered stabilization of Takagi-Sugeno fuzzy systems with actuator saturation are investigated in this paper. Different from the existing quadratic event-triggered mechanism (ETM), a linear ETM is constructed, which can be reduced to a time-triggered mechanism (TTM). Based on parallel distribution compensation, an event-triggered fuzzy controller is designed, and sufficient conditions under the estimation of a certain domain of attraction are proposed to ensure the ETM-based and TTM-based closed-loop systems are positive and stable. The controller gain is solved directly by the proposed conditions. And then these sufficient conditions are extended to the conditions under the estimation of the largest domain of attraction by establishing an optimization problem. Furthermore, the linear ETM is proved to exclude the Zeno behavior of the system. Finally, two simulation examples are utilized to verify the effectiveness of the proposed event-triggered control scheme.

Practical finite‐time fuzzy control of uncertain nonstrict‐feedback systems with actuator saturation and output constraints

SummaryThis article investigates the devise issue of a practical finite‐time output‐tracking control for uncertain nonlinear nonstrict‐feedback systems subject simultaneously to time‐varying output constraints (TVOC), actuator saturation, and bounded unmatched disturbances. An adaptive fuzzy approximator‐based control system is devised using the dynamic surface control (DSC) concept. System output constraints are addressed by employing an appropriate barrier Lyapunov function. Adaptive fuzzy disturbance observers are constructed to practically deal with time‐varying unmatched but bounded disturbances. It is verified via Lyapunov stability analysis and simulation experiments that all closed‐loop signals remain bounded, the output tracking error practically converges in finite time to a tiny but adjustable neighborhood around the origin, and the system output stays within its required time‐varying bounds.

Fuzzy control of singular fractional order multi-agent systems with actuator saturation

In this paper, a T-S fuzzy model is established to describe nonlinear fuzzy singular fractional order multi-agent systems (SFOMASs) exhibiting actuator saturation when the order is between 0 and 2. We focus on the case where the system state is difficult to measure or cannot be directly measured, so it needs to be estimated based on other measurable signals. To this end, a fuzzy observer is designed, which can process fuzzy or imprecise input and output signals through fuzzy processing. Then the observer-based leader-following consensus problem of fuzzy SFOMASs with actuator saturation is addressed. To address input saturation, we use some mathematical tools to represent the saturated linear feedback on the convex hull, which is then transformed into seeking the optimal solution of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is verified through the adoption of a numerical example.

Nonsingular fast terminal sliding mode tracking control for underwater glider with actuator physical constraints

An adaptive finite-time composite control (AFTCC) scheme is designed for the pitch angle trajectory tracking control of Underwater Glider (UG) with actuator physical constraints, uncertain dynamics and external disturbances. Firstly, a novel nonsingular fast terminal sliding mode control (NFTSMC) law is designed that can avoid singular problems, significantly reduce chattering, and achieve finite-time convergence of the system states. Secondly, a novel fixed-time extended state observer (FxTESO) is established to estimate the pitch angular velocity and lumped disturbances within a fixed time. Furthermore, a novel adaptive fixed-time saturation compensation system (AFxTSCS) is proposed to mitigate the effect caused by actuator saturation, and it can adjust the parameter adaptively when the actuator is in saturation or out of saturation. Finally, the AFTCC scheme, which is based on the NFTSMC framework and combines FxTESO and AFxTSCS, is designed to achieve the pitch angle trajectory tracking of UG, and the finite-time convergence of the whole closed-loop system is proved by the Lyapunov stability theory, and the simulations verify the availability and superiority of the proposed AFTCC scheme.

L2$$ {L}_2 $$‐gain analysis and fault‐tolerant control for nonlinear discrete‐time switched systems with time‐varying delay and actuator saturation

AbstractThe ‐gain analysis and fault‐tolerant control of a class of uncertain nonlinear discrete‐time switched systems with time‐varying delay and actuator saturation are studied by using the multiple Lyapunov functions method. The fault‐tolerant state feedback controllers and the switching law are designed such that the closed‐loop system with actuator failures satisfies the disturbance attenuation performance indicator. The problem of estimating the capacity of admissible disturbance is transformed into a constrained optimization problem to ensure that the state trajectory of the closed‐loop system is bounded under the action of external disturbances. The upper bound of restricted ‐gain is estimated by solving constrained optimization problems. Then, when the fault‐tolerant controller can be regard as the design variable, the optimization problems above are adjusted for solving control synthesis problems. Finally, the numerical example is given to verify the effectiveness of the design method.

Adaptive Tracking Control of Robotic Manipulator Subjected to Actuator Saturation and Partial Loss of Effectiveness

Abstract This paper introduces an adaptive control design tailored for robotic systems described by Euler–Lagrange equations under actuator saturation and partial loss of effectiveness. The adaptive law put forth not only retains conventional control properties but also extends its scope to effectively address challenges posed by actuator saturation and partial loss of effectiveness. The framework’s primary focus is on bolstering system robustness, thereby ensuring the achievement of uniformly ultimate bounded tracking errors. The stability and convergence of the system’s behavior are rigorously established through the application of the Lyapunov analysis technique. Moreover, the effectiveness and superiority of the introduced framework are compellingly demonstrated through a series of practical simulations and experimental instances.

Analysis of virtual inerter-based passive absorber for active chatter control

This paper presents a novel approach to active chatter control in milling operations using a new concept called the virtual inerter-based dynamic vibration absorber (VIDVA). While passive control methods, such as tuned mass damper (TMDs), have their merits, they may not provide optimal performance and adaptability in certain scenarios. Moreover, the realisation of an idealised inerter-based absorber as a localisation addition can be a difficult task to achieve. In response of these challenges, the integration of the inerter concept into virtual passive absorber (VPA) control to improve chatter stability performance is proposed. Four IDVAs are numerically evaluated to enhance the absolute chatter stability limit, and the numerical results are experimentally validated using cutting tests with a proof-mass actuator providing the control force. The study also includes robustness and actuator saturation analysis to provide a comprehensive evaluation of the proposed virtual IDVA. The findings demonstrate that the virtual IDVA offers improved chatter suppression performance, making it a promising solution for active chatter control and application of IDVAs in milling operations.

Distributed Dynamic Surface Control for a Class of Quadrotor UAVs with Input Saturation and External Disturbance

An adaptive dynamic surface trajectory tracking control method based on the Nussbaum function is proposed for a class of quadrotor UAVs encountering unknown external disturbances and unidentified nonlinearities. By transforming controller expressions into numerical solutions, the challenge of overly complex controller design expressions is addressed, simplifying the overall controller design process and enhancing the efficiency of simulation programs. Additionally, an adaptive controller based on Nussbaum gain is introduced to effectively resolve actuator saturation issues. This approach mitigates complexities associated with traditional control design and ensures smooth operation of the quadrotor UAVs. The proposed methodology offers promising prospects for enhancing the robustness and performance of quadrotor UAVs under uncertain operating conditions. Finally, to validate the effectiveness of the proposed control scheme, a hardware-in-the-loop experimental setup is constructed. The dynamic model of the quadrotor UAVs and the proposed controller scheme are implemented on the Rapid Control Prototype (RCP) and Real-Time Simulator (RTS), respectively. This facilitates a semi-physical simulation experiment, providing a basis for the subsequent application of the control scheme to actual aerial vehicles. The concluding experimental results affirm the effectiveness of the proposed control scheme and highlight its potential for practical applications.

Distributed Lyapunov-Based Model Predictive Control for AUV Formation Systems with Multiple Constraints

This paper focuses on the formation tracking issue of autonomous underwater vehicles (AUVs) subject to multiple constraints in three-dimensional space. We developed a novel distributed Lyapunov-based model predictive controller (DLMPC) with a fast finite-time extended state observer (FFTESO). Initially, the external disturbances and internal uncertainties of each AUV were precisely compensated using the designed FFTESO. Subsequently, we proposed DLMPC-based position tracking and velocity tracking controllers, which solved an online optimization problem to determine optimal velocities and control forces. This hierarchical framework effectively managed system constraints, such as state constraints and actuator saturation. Additionally, the Lyapunov-based backstepping control law was applied to construct stability constraints in the distributed optimization problem, ensuring the recursive feasibility and closed-loop system stability of the proposed scheme. Sufficient conditions and attraction regions to ensure stability were explicitly provided. Finally, the simulation results demonstrated that the proposed method improved both the convergence speed and tracking accuracy by at least 30% compared to other methods.

Fully actuated system approach for spacecraft rendezvous system with actuator saturation

This paper explores the application of a fully actuated system (FAS) approach to a spacecraft rendezvous system with actuator saturation. A FAS model for the spacecraft rendezvous system is developed, followed by the design of an extended state observer (ESO) to estimate unmeasurable states and the system's nonlinear terms. The saturation issue is addressed using the convex hull method. By the designed ESO, a state feedback controller for the system is designed using the FAS approach, resulting in a constant linear closed-loop system whose eigenvalues can be arbitrarily assigned. This method simplifies the controller design process and provides a more accurate system model without the linearisation of nonlinear terms, thereby improving control accuracy. Simulation results show the effectiveness and usefulness of the proposed method.

A unified study of the redundant control input problem with different conditions in the stabilizable case

This paper investigates the redundant control input problem in the sense of linear quadratic regulator optimal control. Increasing redundant control inputs leads to a decrease in the quadratic performance index. However, in some cases, this also increases the norm of the feedback matrix, resulting in actuator saturation. To solve the problem, a comparative analysis of the latest research results on the redundant control input problem under different conditions is first presented. Secondly, new tighter upper bounds of the positive (semi-)definite solution of the continuous algebraic Riccati equation (CARE) corresponding to the redundant control input problem are studied uniformly in the stabilizable case. Thirdly, based on them, a class of sufficient conditions to guarantee that the norm of the feedback matrix decreases is presented. Finally, numerical experiments demonstrate the effectiveness and superiority of our conclusions. Meanwhile, a simulation experiment demonstrates that systems with redundant control inputs can achieve good control performance.

Exponential synchronization of nonlinear dynamical systems via an aperiodic hybrid control with actuator saturation and impulse time windows

AbstractConsidering impulse time windows and the actuator saturation, we put forward a novel aperiodic hybrid control scheme to achieve the exponential synchronization of two nonlinear dynamical systems (NDSs). Different from the existing research, the actuator saturation of two types of control signals and impulse time windows are both considered in the exponential synchronization analysis. Some sufficient conditions are found with designing the hybrid controller, and the attraction domain (AD) of the error system is also estimated. On the other hand, the conditions which can ensure the exponential synchronization between two NDSs with this hybrid control without saturation limit are also given. Finally, experimental results for the synchronization of three dimensional Hopfield‐type neural networks and the image reproduction based on the synchronization of neural networks demonstrate the feasibility of our theoretical results.

Adaptive fuzzy sliding mode control of uncertain nonholonomic wheeled mobile robot with external disturbance and actuator saturation

This paper developed a modified barrier function-based adaptive sliding mode control (MBFASMC) method to improve the tracking precision and robustness performance of the nonholonomic wheeled mobile robot (NWMR), which is subject to actuator saturation and external disturbance. Owing to the modified positive semi-definite barrier function (MPSDBF), the requirement for disturbance bound and the overestimation of control gain are eliminated. The nonsingular terminal sliding manifold and MPSDBF-based adaptive mechanism can guarantee that the sliding variables and the posture errors of NWMR converge to precisely predefined ultimate bounds in a finite time. In order to compensate for the adverse effect of input saturation, an auxiliary dynamics is proposed based on saturation error and used to construct the MBFASMC. Compared to the recent anti-saturation control methods, the demand for saturation level is released in the proposed control method. Moreover, a modified barrier function-based adaptive fuzzy sliding mode control (MBFAFSMC) is provided to relieve the control chattering problem. By Lyapunov analysis, it is validated that the proposed methods can ensure the pre-specified and finite-time convergence performance of the uncertain NWMR. The MBFASMC and MBFAFSMC are also applied to an actual NWMR experimental platform with artificial disturbances to verify the effectiveness of the proposed methods.

Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation

AbstractThis paper investigates an event‐triggered adaptive resilient control problem for nonlinear systems against unknown false data injection and actuator saturation. The sensors of the controlled system are subject to unknown false data injection attacks so that all original states can not be directly applied in the controller design process. To address the negative effects of the false data injection attacks, attack compensators are introduced in control design. Simultaneously, a dynamic event‐triggering mechanism is set up to reduce the communication burden of the network. Furthermore, an auxiliary system is constructed to cope with the actuator saturation that commonly exists in practical systems. Based on the Lyapunov stability theory, it is demonstrated that the designed adaptive controller can guarantee the stability of the controlled system and the boundedness of all signals. The validity of the proposed control scheme is evidenced by simulation examples.

A Fixed-Time Multi-Platoon Maneuvers with Actuator Saturation and Faults

A Fixed-Time Multi-Platoon Maneuvers with Actuator Saturation and Faults

Event-triggered regional stabilization for T–S fuzzy systems subject to communication delays and actuator saturations

This paper considers the regional stabilization problem for networked T–S fuzzy systems with communication delays and actuator saturations under the event-triggered mechanism. Using a piecewise augmented Lyapunov–Krasovskii functional, the modified local sector condition, as well as the Wirtinger-based inequality, a stability criterion is first proposed such that the closed-loop system is exponentially stable for any initial condition satisfying certain constraint. Then, the stabilization criterion is provided according to the solvability of linear matrix inequalities. Furthermore, the optimization problem of the region of initial conditions is explicitly discussed. Finally, a benchmark example is presented to show the applicability of the obtained result.

Fault-Tolerant Fuzzy-Resilient Control for Fractional-Order Stochastic Underactuated System With Unmodeled Dynamics and Actuator Saturation.

This article is considered on underactuated fractional-order stochastic systems (FOSSs) with actuator saturation and incrementally conic nonlinear terms, whose fractional-order α ∈ (0,1) . First, to bring FO dynamic signals, solving the unmodeled dynamics, in the meantime, the saturated nonlinear term of the control input is taken into account. At the time, to cope with the stability issue of FOSS under such situation, the fault tolerant resilient controller based on underactuated condition is designed. Then, according to the method of the Lyapunov and It∧ o differential formulation to design proper multiple Lyapunov-Krasovskii (L-K) functions, such that, a novel sufficient condition of the robustly asymptotically stability of fuzzy FOSS under underactuated conditions is rigorously proved in terms of linear matrix inequality (LMI). Furthermore, in order to research the mean square stability of the above-mentioned system, so the solution of FOSS is obtained to achieve this purpose. By applying the above method, which is proposed in this work that the controlled system can be obtained with faster response and higher control accuracy. At last, to display the superiority of the above-mentioned scheme is effective, tethered satellite system and numerical results are presented.

B-Spline Wavelet Neural-Network-Based Adaptive Control for Linear-Motor-Driven Systems via a Novel Gradient Descent Algorithm

This paper proposes a gradient descent (GD) algorithm-based B-Spline wavelet neural network (GDBSWNN) learning adaptive controller for linear motor (LM) systems under system uncertainties and actuator saturation constraints. A recursive least squares (RLS) algorithm-based indirect adaptive strategy is used to effectively estimate model parameters, which can guarantee they converge to true values. A novel GDBSWNN compensator is proposed to estimate the remaining complex uncertainties, where weights are updated by online GD training. An auxiliary system is integrated into the control scheme to address the saturation problem, which guarantees stability and satisfactory control performance when saturation occurs. In addition, a stability analysis is presented to prove that all signals of the closed-loop system are bounded using the Lyapunov theory. Experiments have been conducted on an LM-driven motion platform, where different controllers have been tested, demonstrating the effectiveness and advantages of the proposed approach.

Adaptive anti‐windup output feedback control for nonlinear systems and its stability analysis

SummaryIn the practical application of adaptive control methods, a windup phenomenon for the systems with input saturation may occur because there exists an input restriction such as saturation of actuator in most actual systems due to physical reasons. In this paper, to alleviate the influence of the windup phenomenon by input saturation, we propose an output feedback exponentially passive (OFEP)‐based adaptive model recovery anti‐windup (AMRAW) control strategy for the stable nonlinear systems with input saturation. Moreover, in order to realize an augmented OFEP system for non‐OFEP nonlinear systems that do not satisfy the OFEP properties, a parallel feedforward compensator (PFC) is introduced, and a radial basis function (RBF) neural network (NN)‐based adaptive feedforward input is designed to attain accurate tracking performance for systems with the PFC. Furthermore, the detailed stability analysis of the proposed AMRAW control system is provided, and the performance of the proposed method is validated through appropriate numerical simulations.