Adaptive finite-time prescribed performance control for stochastic nonlinear systems with unknown virtual control coefficients

Nonlinear Dynamics - This paper is devoted to the adaptive finite-time prescribed performance control (FTPPC) for stochastic nonlinear systems with unknown virtual control coefficients (UVCCs),...     

Adaptive prescribed performance control for nonlinear pure-feedback systems: a scalarly virtual parameter adaptation approach

Nonlinear Dynamics - In this paper, an adaptive prescribed performance controller, consisting of a novel scalarly virtual parameter adaptation (SVPA) technique, is developed for a class of...     

Robust dynamic surface control of nonlinear systems with prescribed performance

In this paper, a robust dynamic surface controller with prescribed performance for a class of nonlinear feedback systems is proposed. Utilizing the prescribed performance control (PPC), the prescribed steady state and transient performance for the tracking error of the original system can be ensured through the stabilization of a transformed system. The dynamic surface control procedure solves the mismatched uncertainties and the explosion of the complexity problem. The uncertainties can be eliminated by the constructed compensation signals of a low-pass filter. And it is proven in the performance analysis that the proposed controller is of low complexity and has improved system robustness. Simulation results verify the proposed approach.     

Adaptive neural novel prescribed performance control for non-affine pure-feedback systems with input saturation

An error constraint control problem is considered for pure-feedback systems with non-affine functions being possibly in-differentiable. A new constraint variable is used to construct virtual control that guarantees the tracking error within the transient and steady-state performance envelopment. The new error transformation avoids non-differentiable problems and complex deductions caused by traditional error constraint approaches. A locally semi-bounded and continuous condition for non-affine functions is employed to ensure the controllability and transform the closed-loop system into a pseudo-affine form. An auxiliary system with bounded compensation term is proposed for nonlinear systems with input saturation. On the basis of backstepping technique, an adaptive neural controller is designed to handle unknown terms and circumvent repeated differentiations of virtual controls. The boundedness and convergence of the closed-loop system are proved by Lyapunov theory. Asymptotic tracking is achieved without violating control input constraint and error constraint. Two examples are performed to verify the theoretical findings.     

Adaptive robust maneuvering control for nonlinear systems via dynamic surface technique

In this paper, the adaptive robust controller based on dynamic surface technique is investigated for the maneuvering problem of uncertain nonlinear systems with external disturbances. As preliminary, the definition of semi-globally uniformly practically asymptotically stable and its Lyapunov criterion are presented. The static part of controller with smooth robust compensator and adaptive law is designed to achieve the geometric task of maneuverability, and the dynamic control is proposed to reach the speed task by filtered-gradient update law. Moreover, utilizing first-order filter, the problem of “dimensional explosion” is avoided in controller design. Simulation is conducted for three-mecanum-wheeled mobile robot actuated by DC motors to illustrate the effectiveness of the control strategy.

     

Fault tolerant robust control with transients for over-actuated nonlinear systems

Nonlinear Dynamics - For the problem of robust fault tolerant control of over-actuated nonlinear systems, a new robust synthesis method is investigated. The nonlinear system is modeled via a...     

Adaptive smooth control for nonlinear uncertain systems

Nonlinear Dynamics - This paper presents an adaptive smooth controller for a class of nonlinear dynamical systems in the presence of bounded uncertainties with unknown bounds. Motivated by the...     

Observer-based event-triggered adaptive containment control for multiagent systems with prescribed performance

Nonlinear Dynamics - This paper focuses on the problem of the event-triggered adaptive containment control for a class of nonlinear multiagent systems (MASs) with prescribed performance and...     

Extended state observer-based adaptive prescribed performance control for a class of nonlinear systems with full-state constraints and uncertainties

Nonlinear Dynamics - In this paper, an extended state observer-based adaptive prescribed performance control technique is proposed for a class of nonlinear systems with full-state constraints and...     

Adaptive finite-time event-triggered command filtered control for nonlinear systems with unknown control directions

Nonlinear Dynamics - In this article, we study an adaptive finite-time event-triggered command filtered control problem based on output feedback for a class of nonstrict-feedback nonlinear systems...     

Event-driven-observer-based fuzzy fault-tolerant control for nonlinear system with actuator fault

Nonlinear Dynamics - In this study, a novel fuzzy logic-aided event-driven-observer-based fault-tolerant control approach is investigated for a class of nonlinear systems with time-varying actuator...     

Adaptive sliding mode disturbance observer-based composite trajectory tracking control for robot manipulator with prescribed performance

Nonlinear Dynamics - In this paper, the problem of the composite trajectory tracking control for robot manipulator with lumped uncertainties including unmodeled dynamics and external disturbances...     

Adaptive robust fuzzy control for a class of uncertain chaotic systems

In this paper, the output feedback control of uncertain chaotic systems is addressed via an adaptive robust fuzzy approach. Fuzzy logic systems are employed to approximate uncertain nonlinear functions in the chaotic systems. Because only partial information of the system’s states is needed to be known, an observer is given to estimate the unmeasured states. Compared with the existing results in the observer design, the prior knowledge on dynamic uncertainties is relaxed and a class of more general chaotic systems is considered as well as robustness to the approximation error is improved. It can be proven that the closed-loop system is stable in the sense that all the variables are bounded. Simulation example for the unified chaotic systems is given to verify the effectiveness of the proposed method. This work was supported in part by the National Natural Science Foundation of China (60874056) and the Foundation of Educational Department of Liaoning Province (2008312).