Online fault compensation control based on policy iteration algorithm for a class of affine non-linear systems with actuator failures

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 algorith...

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Bibliographic Details
Published in:IET control theory & applications Vol. 10; no. 15; pp. 1816 - 1823
Main Authors: Zhao, Bo, Liu, Derong, Li, Yuanchun
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 10.10.2016
Subjects:
Actuator failure
actuator failures
affine nonlinear systems
Algorithms
approximate optimal control policy
asymptotic stability
Compensation
critic neural network
Dynamical systems
fault compensation control scheme
fault detection and isolation mechanism
fault tolerant control
Faults
fault‐free dynamic models
Hamilton‐Jacobi‐Bellman equation
iterative methods
Lyapunov direct method
Lyapunov methods
Mathematical models
neurocontrollers
nonlinear control systems
Nonlinear dynamics
online fault compensation control
optimal control
Policies
policy iteration algorithm
Research Article
online fault compensation control
fault compensation control scheme
iterative methods
approximate optimal control policy
fault-free dynamic models
optimal control
asymptotic stability
fault detection and isolation mechanism
critic neural network
affine nonlinear systems
Hamilton-Jacobi-Bellman equation
neurocontrollers
nonlinear control systems
actuator failures
PI
policy iteration algorithm
Lyapunov direct method
fault tolerant control
Lyapunov methods
ISSN:1751-8644, 1751-8652
Online Access:Get full text
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Summary: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.
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ISSN:1751-8644
1751-8652
DOI:10.1049/iet-cta.2015.1105