Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems
This paper proposes an NN-based cooperative control scheme for a type of continuous nonlinear system. The model studied in this paper is designed as an interconnection topology, and the main consideration is the connection mode of the undirected graph. In order to ensure the online sharing of learni...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2021/5535971 |
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| _version_ | 1850178182350635008 |
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| author | Siyu Gao Xin Wang |
| author_facet | Siyu Gao Xin Wang |
| author_sort | Siyu Gao |
| collection | DOAJ |
| description | This paper proposes an NN-based cooperative control scheme for a type of continuous nonlinear system. The model studied in this paper is designed as an interconnection topology, and the main consideration is the connection mode of the undirected graph. In order to ensure the online sharing of learning knowledge, this paper proposes a novel weight update scheme. In the proposed update scheme, the weights of the neural network are discrete, and these discrete weights can gradually approach the optimal value through cooperative learning, thereby realizing the control of the unknown nonlinear system. Through the trained neural network, it is proved if the interconnection topology is undirected and connected, the state of the unknown nonlinear system can converge to the target trajectory after a finite time, and the error of the system can converge to a small neighbourhood around the origin. It is also guaranteed that all closed-loop signals in the system are bounded. A simulation example is provided to more intuitively prove the effectiveness of the proposed distributed cooperative learning control scheme at the end of the article. |
| format | Article |
| id | doaj-art-c4d93098b7944c268d2b723163489f6f |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-c4d93098b7944c268d2b723163489f6f2025-08-20T02:18:47ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2021-01-01202110.1155/2021/55359715535971Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear SystemsSiyu Gao0Xin Wang1Chongqing Key Laboratory Nonlinear Circuits & Intelligent, Southwest University, Chongqing 400715, ChinaChongqing Key Laboratory Nonlinear Circuits & Intelligent, Southwest University, Chongqing 400715, ChinaThis paper proposes an NN-based cooperative control scheme for a type of continuous nonlinear system. The model studied in this paper is designed as an interconnection topology, and the main consideration is the connection mode of the undirected graph. In order to ensure the online sharing of learning knowledge, this paper proposes a novel weight update scheme. In the proposed update scheme, the weights of the neural network are discrete, and these discrete weights can gradually approach the optimal value through cooperative learning, thereby realizing the control of the unknown nonlinear system. Through the trained neural network, it is proved if the interconnection topology is undirected and connected, the state of the unknown nonlinear system can converge to the target trajectory after a finite time, and the error of the system can converge to a small neighbourhood around the origin. It is also guaranteed that all closed-loop signals in the system are bounded. A simulation example is provided to more intuitively prove the effectiveness of the proposed distributed cooperative learning control scheme at the end of the article.http://dx.doi.org/10.1155/2021/5535971 |
| spellingShingle | Siyu Gao Xin Wang Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems Discrete Dynamics in Nature and Society |
| title | Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems |
| title_full | Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems |
| title_fullStr | Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems |
| title_full_unstemmed | Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems |
| title_short | Neural-Network-Based Collaborative Control for Continuous Unknown Nonlinear Systems |
| title_sort | neural network based collaborative control for continuous unknown nonlinear systems |
| url | http://dx.doi.org/10.1155/2021/5535971 |
| work_keys_str_mv | AT siyugao neuralnetworkbasedcollaborativecontrolforcontinuousunknownnonlinearsystems AT xinwang neuralnetworkbasedcollaborativecontrolforcontinuousunknownnonlinearsystems |