An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach

Seung Jin Chang, Jae Young Lee, Jin Bae Park, Yoon Ho Choi

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

In this paper, we propose an actor-critic neuro-control for a class of continuous-time nonlinear systems under nonlinear abrupt faults, which is combined with an adaptive fault diagnosis observer (AFDO). Together with its estimation laws, an AFDO scheme, which estimates the faults in real time, is designed based on Lyapunov analysis. Then, based on the designed AFDO, a fault tolerant actor- critic control scheme is proposed where the critic neural network (NN) is used to approximate the value function and the actor NN updates the fault tolerant policy based on the approximated value function in the critic NN. The weight update laws for critic NN and actor NN are designed using the gradient descent method. By Lyapunov analysis, we prove the uniform ultimately boundedness (UUB) of all the states, their estimation errors, and NN weights of the fault tolerant system under the unpredictable faults. Finally, we verify the effectiveness of the proposed method through numerical simulations.

Original languageEnglish
Pages (from-to)311-318
Number of pages8
JournalInternational Journal of Control, Automation and Systems
Volume13
Issue number2
DOIs
Publication statusPublished - 2015 Apr 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

Fingerprint Dive into the research topics of 'An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach'. Together they form a unique fingerprint.

  • Cite this