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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8418692/ |
_version_ | 1819171720502706176 |
---|---|
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. |
first_indexed | 2024-12-22T19:55:46Z |
format | Article |
id | doaj.art-f019fc7b45064ad0adccc2a68dc67c45 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-22T19:55:46Z |
publishDate | 2018-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
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 |