Open AccessOnline fault compensation control based on policy iteration algorithm for a class of affine non‐linear systems with actuator failures
Author(s) -
Zhao Bo,
Liu Derong,
Li Yuanchun
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.1105
Subject(s) - control theory (sociology) , affine transformation , actuator , compensation (psychology) , fault (geology) , computer science , lyapunov function , fault detection and isolation , artificial neural network , lyapunov stability , nonlinear system , mathematics , control (management) , artificial intelligence , psychology , seismology , psychoanalysis , pure mathematics , geology , physics , quantum mechanics
In this study, a novel online fault compensation control scheme based on policy iteration (PI) algorithm is developed for a class of affine non‐linear systems with actuator failures. The control scheme consists of a PI algorithm and a fault compensator. For fault‐free dynamic models, the PI algorithm is developed to solve the Hamilton–Jacobi–Bellman equation by constructing a critic neural network, and then the approximate optimal control policy can be derived directly. Alternatively, the actuator failure is reconstructed adaptively to achieve online fault compensation without the fault detection and isolation mechanism. The closed‐loop system is proved to be asymptotically stable via Lyapunov's direct method. Two numerical simulation examples are given to demonstrate the effectiveness of the proposed fault compensation control scheme.