Adaptive optimal fault-tolerant control scheme for a class of strict-feedback nonlinear systems

Abstract

An active optimal fault-tolerant control (FTC) scheme for a class of nonlinear systems in strict-feedback form in the presence of partial loss of actuator effectiveness faults is proposed, using backstepping design technique and adaptive dynamic programming (ADP) algorithm to compensate the effects of failure. The proposed FTC scheme consists of feedforward controller that achieve the objective of fault-tolerant and feedback optimal controller, which can guarantee the performance index function is minimized. Since fault estimation and control law parameters are updated online, the control system has an adaptive failure compensation capability so as to reconfigure the control law in real time in response to failure indications. Based on Lyapunov stability theory, the whole closed-loop system is guaranteed to be ultimately uniformly bounded. Finally, the effectiveness of the proposed method is demonstrated by simulation.

An integrated structure of operational performance-oriented monitoring and degradation recovery based on iterative adaptive dynamic programming

“…Theoretically, iterative adaptive dynamic programming (ADP) has been evolved from reinforcement learning approaches for optimal controller design. In addition, the iterative ADP-based approaches have been used in optimal design of continuous or discrete-time systems (Liu et al, 2017; Ren et al, 2020), and nonlinear optimum control with input/output constraints, external disturbances, and actuator faults (Dai et al, 2019; Liu et al, 2020; Wang et al, 2017; Zhang et al, 2019). However, the majority of current studies focus on system performance degradation caused by component-level faults, and there is insufficient research on the recovery of overall performance degradation caused by the abnormal conditions which affects the quality of final product directly.…”

Multiplayer zero‐sum games optimal control for modular robot manipulators with interconnected dynamic couplings

“…As one of the effective methods to deal with above problem, ADP is used to address HJ/HJI equations. Furthermore, ADP theory is a key direction to undertake approximate optimal control system issues of discrete‐time, 4‐6 continuous‐time, 7‐9 data driven 10‐12 and furthermore robot systems with constraints, 13‐15 uncertainties 16‐18 as well as actuator failures 19‐21 . Zhang et al 22 developed a resilient event‐triggered approximate optimal control for autonomous vehicle.…”

“…This completes the proof. Based on compensator control law (19) and approximated control policy (26), one has completed optimal control law as follows:…”

Decentralized position–force zero-sum approximate optimal control for reconfigurable robots with unmodeled dynamic

“…Optimal control method has been proposed nearly 70 years ago (Bellman and Dreyfus, 2013; Pontryagin, 1959), and plenty of literatures are recorded (An et al, 2021; An et al, 2021; Wei et al, 2021). Adaptive dynamic programming (ADP) theory is a key direction to undertake approximate optimal control system issues of discrete-time (Hu et al, 2021; Luo et al, 2020; Zhu et al, 2020a), continuous-time (An et al, 2021; Shan et al, 2020; Wei et al, 2020), data driven (Gao et al, 2018; Li et al, 2020; Su et al, 2020), and furthermore robot systems with input/output constraints (An et al, 2020; Lu et al, 2020; Ren et al, 2019), external disturbance (An et al, 2019; Song and Lewis, 2020; Xia et al, 2020), actuator failures (Dai et al, 2018; Jiao et al, 2018; Ma et al, 2020), and so on. Kong et al (2021b) developed n -link manipulator approximate optimal law via saturation nonlinearity.…”