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 language | English |
|---|---|
| Pages (from-to) | 311-318 |
| Number of pages | 8 |
| Journal | International Journal of Control, Automation and Systems |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2015 Apr 1 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications
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An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach. / Chang, Seung Jin; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho.
In: International Journal of Control, Automation and Systems, Vol. 13, No. 2, 01.04.2015, p. 311-318.Research output: Contribution to journal › Article
TY - JOUR
T1 - An online fault tolerant actor-critic neuro-control for a class of nonlinear systems using neural network HJB approach
AU - Chang, Seung Jin
AU - Lee, Jae Young
AU - Park, Jin Bae
AU - Choi, Yoon Ho
PY - 2015/4/1
Y1 - 2015/4/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84939978194&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84939978194&partnerID=8YFLogxK
U2 - 10.1007/s12555-014-0034-3
DO - 10.1007/s12555-014-0034-3
M3 - Article
AN - SCOPUS:84939978194
VL - 13
SP - 311
EP - 318
JO - International Journal of Control, Automation and Systems
JF - International Journal of Control, Automation and Systems
SN - 1598-6446
IS - 2
ER -