Control Of Nonlinear Systems Research Articles

Continuous predefined-time sliding mode control for second-order nonlinear systems under full-channel disturbances

This paper presents a continuous predefined-time sliding mode control (CPTSMC) strategy for second-order nonlinear systems subject to full-channel disturbances. A predefined-time extended state observer (PTESO) is derived to estimate both the unknown system states and disturbances, with the upper bound for the settling time (UBST) precisely defined by one design parameter in a less conservative manner than those of finite-time or fixed-time ESOs. Furthermore, the peak observation errors are small during the transient process. Then, using the estimates, a CPTSMC law is designed for the chattering-alleviated predefined-time convergence of system states. The internal mechanism of parameter tuning for improving transient performance is theoretically explored. In addition to proving that the UBST of the whole system is precisely defined by one design parameter, we show the continuity of CPTSMC and the boundedness of all system signals that are vital for practical applications. Ultimately, the proposed approach is applied to a DC servo motor to demonstrate its efficiency.

Adaptive fuzzy command filtered control for uncertain fractional order nonlinear systems with full state constraints

This paper investigates the tracking control problem for fractional-order (FO) nonlinear systems with model uncertainties and external disturbances under full-state constraints. An adaptive fuzzy control strategy based on a command filter is proposed, where the asymmetric Barrier Lyapunov Function is adopted to ensure that the states do not violate their constraints, and a fuzzy logic system is used to approximate the unknown nonlinear terms. Additionally, a FO command filter is implemented to approximate the virtual control signals and their derivatives, effectively addressing the explosion of complexity problem, while an error compensation function is incorporated to compensate for the filtering errors. Overall, the stability analysis is conducted based on the Lyapunov method to ensure the boundedness of all signals. Ultimately, the performance of the proposed controller is demonstrated through two simulation examples.

Approximate controllability of nonlinear evolution fractional control system with delay

Approximate controllability of nonlinear evolution fractional control system with delay

Adaptive event-triggered control for nonstrict-feedback nonlinear systems with time-varying delay and uncertain nonlinearities: A neural network approach

Adaptive event-triggered control for nonstrict-feedback nonlinear systems with time-varying delay and uncertain nonlinearities: A neural network approach

Fault Detection Observer Design for Nonlinear Steering Control Systems of Unmanned Surface Vehicles

ABSTRACTThis article studies the design of fault detection (FD) observers for nonlinear steering control (NSC) systems of unmanned surface vehicles (USVs) with steering machine faults. The considered NSC systems of USVs are characterized by discrete‐time T‐S fuzzy models with immeasurable states. First, a new fuzzy FD observer is constructed to handle the challenge caused by the introduction of membership functions (MFs) that are different from the ones in the system, in which the MFs in the FD are designed by scaling and biasing those of the T‐S model. Different from the existing uncertainty restrictions between the MFs in the systems and those in the observers, the deterministic restrictions are constructed, and the MFs of the observer are directly constructed according to the ones of the system without calculation. Then, by employing Lyapunov function (LF), it is proved that the constructed FD observers can ensure the stability and desired performance of the systems. Finally, an NSC system model of USVs is given to verify the effectiveness of the presented technical solution.

Resilient stepped transmission and control for nonlinear systems against DoS attacks

In this paper, we focus on developing a resilient stepped transmission scheme for nonlinear networked systems suffering from Denial-of-Service (DoS) attacks. Instead of employing static periodic sampling, the proposed acknowledgement-based adaptive sampler follows a resilient stepped algorithm to dynamically adjust the sampling period based on the absence or presence of DoS attacks. The dynamic sampling period is demonstrated to approach the boundary sampling interval to better adapt to the vulnerable environment, where the boundary sampling interval is the largest sampling period to ensure the boundedness of successful transmission interval in conventional periodic sampling scheme. Two impulsive observer-based control structures are presented to ensure the asymptotic stability of the equilibrium of systems, in which the latter one can better cope with the amplification of observer error in the presence of DoS. Numerical simulations are given finally to substantiate the validity of theoretical results.

Hierarchical Control of Nonlinear Uncertain Active Suspension System Based on Extended State Observer

Hierarchical Control of Nonlinear Uncertain Active Suspension System Based on Extended State Observer

Dual-channel triggered fuzzy adaptive output feedback control for uncertain nonlinear systems with deception attacks

Dual-channel triggered fuzzy adaptive output feedback control for uncertain nonlinear systems with deception attacks

Lag formation control for nonlinear second-order multiagent systems without and with external disturbances

Lag formation control for nonlinear second-order multiagent systems without and with external disturbances

Adaptive prescribed performance optimal control for strict-feedback nonlinear systems with input delay and input quantization

Adaptive prescribed performance optimal control for strict-feedback nonlinear systems with input delay and input quantization

Adaptive Fuzzy Control for Stochastic Nonlinear Systems With Delayed Input and Delayed State via Improved Lyapunov–Krasovskii Function

Adaptive Fuzzy Control for Stochastic Nonlinear Systems With Delayed Input and Delayed State via Improved Lyapunov–Krasovskii Function

Time-delay neural network observer-based adaptive finite-time prescribed performance control for nonlinear systems with unknown time-delay

Time-delay neural network observer-based adaptive finite-time prescribed performance control for nonlinear systems with unknown time-delay

Constrained Networked Predictive Control for Nonlinear Systems Using a High-Order Fully Actuated System Approach

Constrained Networked Predictive Control for Nonlinear Systems Using a High-Order Fully Actuated System Approach

A Novel Composite Observer Based Approach for Dynamic Event-Triggered Adaptive Fuzzy Control of Nonlinear Systems Under DoS Attacks

A Novel Composite Observer Based Approach for Dynamic Event-Triggered Adaptive Fuzzy Control of Nonlinear Systems Under DoS Attacks

Adaptive fixed-time control for stochastic nonlinear systems with unknown covariance noise

Adaptive fixed-time control for stochastic nonlinear systems with unknown covariance noise

Complete consensus control of nonlinear cyber-physical systems with two-layer switching networks

The consensus control problem of nonlinear cyber-physical systems with two-layer switching networks is investigated in this paper. Due to the hierarchical structure of two-layer networks, two-layer switching networks can simulate real networks more effectively than single-layer networks. In addition, the nonlinear component of the networks satisfies incremental quadratic constraints. An appropriate Lyapunov function is constructed to provide sufficient conditions for the node-to-node consensus problem. Furthermore, under some given assumptions and the node-to-node consensus, the complete consensus of two-layer networks is achieved. Finally, the validity of the method is verified by a simulation.

Adaptive backstepping fast terminal sliding mode control for nonlinear uncertain active suspension system with mechanical elastic wheel

Adaptive backstepping fast terminal sliding mode control for nonlinear uncertain active suspension system with mechanical elastic wheel

A reinforcement learning methodology to hierarchical sliding‐mode surface H∞$$ {H}_{\infty } $$ control of nonlinear systems via a dynamic event‐triggered mechanism

SummaryThis paper addresses the problem of a hierarchical sliding mode surface (HSMS) control design for nonlinear systems via a dynamic event‐triggered mechanism. Initially, the HSMS containing the system states is constructed to enhance the system's response rate and robustness. By assigning a cost function associated with the HSMS, such an control problem is equivalently transformed into a zero‐sum game problem, where the control policy and the exogenous disturbance are treated as two players with opposite interests. Afterwards, a novel dynamic event‐triggered mechanism is designed, where the triggering condition depends on HSMS variables. To solve the corresponding event‐triggered Hamilton–Jacobi–Isaacs equation, a single‐critic reinforcement learning algorithm is developed, which removes the error generated by approximating the actor network in the actor‐critic network. According to the Lyapunov stability theory, all signals of the considered system are strictly proved to be bounded. Finally, the validity of the proposed control method is demonstrated through simulations of a tunnel diode circuit system and a mass‐spring‐damper system.

Event-triggered adaptive compensation control for stochastic nonlinear systems with multiple failures: An improved switching threshold strategy.

This paper considers the event-triggered adaptive fault-tolerant control (FTC) problem for a class of stochastic nonlinear systems suffering from finite number of actuator failures and abrupt system external failure. Unlike existing event-triggered mechanisms (ETMs), this paper proposes an improved switching threshold mechanism (STM) that effectively addresses the potential system security hazards caused by large signal impulses when both the magnitude size of the controller and its rate of change are too large, while also saving energy consumption. Especially, when the occurrence of both actuator failure and system external failure may lead to over-change rate of the controller, by using the multi-dimensional Taylor network (MTN) approximation technique, the adaptive fault-tolerant control scheme designed based on the improved STM not only has lower resource consumption, but also indirectly improves the control performance of the system by ensuring the system security operation. Not only does it ensure that all signals of the closed-loop system are bounded in probability and the tracking error converges through the proposed control scheme. The feasibility and superiority of the developed scheme is well shown by dynamic model simulations.

Robust controller design based on double-layer nonlinear disturbance observers and sliding mode control for nonlinear systems with mismatched disturbances and uncertainties

Robust controller design based on double-layer nonlinear disturbance observers and sliding mode control for nonlinear systems with mismatched disturbances and uncertainties