Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks

In this paper, a novel observer-based control strategy is proposed for a class of uncertain continuous-time nonlinear systems based on the Hamilton-Jacobi-Bellman (HJB) equation. Due to the complexity of nonlinear systems, the approximately optimal control for affine uncertain continuous-time nonlin...

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Main Authors: Chaoxu Mu, Yong Zhang, Ke Wang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8418692/
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author Chaoxu Mu
Yong Zhang
Ke Wang
author_facet Chaoxu Mu
Yong Zhang
Ke Wang
author_sort Chaoxu Mu
collection DOAJ
description In this paper, a novel observer-based control strategy is proposed for a class of uncertain continuous-time nonlinear systems based on the Hamilton-Jacobi-Bellman (HJB) equation. Due to the complexity of nonlinear systems, the approximately optimal control for affine uncertain continuous-time nonlinear systems is pursued. Considering that only the output variables can be measured in the control practice, the state observer is designed to reconstruct all system states by using the output variables. The observer-based policy iteration algorithm can solve the HJB equation within the adaptive dynamic programming framework for the unknown-state uncertain nonlinear systems, where a critic neural network is constructed to approximate the optimal cost function, and then, the approximate expression of the optimal control policy can be directly derived from solving the HJB equation. In addition, the stability of the whole closed-loop system is provided based on the Lyapunov analysis.
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spelling doaj.art-f019fc7b45064ad0adccc2a68dc67c452022-12-21T18:14:25ZengIEEEIEEE Access2169-35362018-01-016426754268610.1109/ACCESS.2018.28592638418692Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural NetworksChaoxu Mu0https://orcid.org/0000-0003-1055-9513Yong Zhang1https://orcid.org/0000-0003-4385-712XKe Wang2School of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaIn this paper, a novel observer-based control strategy is proposed for a class of uncertain continuous-time nonlinear systems based on the Hamilton-Jacobi-Bellman (HJB) equation. Due to the complexity of nonlinear systems, the approximately optimal control for affine uncertain continuous-time nonlinear systems is pursued. Considering that only the output variables can be measured in the control practice, the state observer is designed to reconstruct all system states by using the output variables. The observer-based policy iteration algorithm can solve the HJB equation within the adaptive dynamic programming framework for the unknown-state uncertain nonlinear systems, where a critic neural network is constructed to approximate the optimal cost function, and then, the approximate expression of the optimal control policy can be directly derived from solving the HJB equation. In addition, the stability of the whole closed-loop system is provided based on the Lyapunov analysis.https://ieeexplore.ieee.org/document/8418692/Adaptive dynamic programming (ADP)adaptive and robust controlneural networksobserversuncertain systems
spellingShingle Chaoxu Mu
Yong Zhang
Ke Wang
Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
IEEE Access
Adaptive dynamic programming (ADP)
adaptive and robust control
neural networks
observers
uncertain systems
title Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
title_full Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
title_fullStr Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
title_full_unstemmed Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
title_short Observer-Based Adaptive Control of Uncertain Nonlinear Systems Via Neural Networks
title_sort observer based adaptive control of uncertain nonlinear systems via neural networks
topic Adaptive dynamic programming (ADP)
adaptive and robust control
neural networks
observers
uncertain systems
url https://ieeexplore.ieee.org/document/8418692/
work_keys_str_mv AT chaoxumu observerbasedadaptivecontrolofuncertainnonlinearsystemsvianeuralnetworks
AT yongzhang observerbasedadaptivecontrolofuncertainnonlinearsystemsvianeuralnetworks
AT kewang observerbasedadaptivecontrolofuncertainnonlinearsystemsvianeuralnetworks