Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems
In this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. It is noted that in the standard backstepping design, the fractional derivative of the virtual quantity needs to be calculated repeatedly, which...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/1270187 |
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| _version_ | 1832548903374815232 |
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| author | Youjun Chen Songyu Wang |
| author_facet | Youjun Chen Songyu Wang |
| author_sort | Youjun Chen |
| collection | DOAJ |
| description | In this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. It is noted that in the standard backstepping design, the fractional derivative of the virtual quantity needs to be calculated repeatedly, which will lead to a sharp increase in the number of controller terms with the increase of the system dimension and finally make the control system difficult to bear. To handle the estimation error, certain robust terms in the controller at the last step are designed. The stability of the controlled system is proven strictly. In addition, the proposed controller has a simple form which can be easily implemented. Finally, in order to verify our theoretical method, the control simulation based on a fractional-order chaotic system is implemented. |
| format | Article |
| id | doaj-art-8fa66ad7a4244178abff2f91ea667603 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8fa66ad7a4244178abff2f91ea6676032025-02-03T06:12:51ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/12701871270187Neural Network Backstepping Controller Design for Fractional-Order Nonlinear SystemsYoujun Chen0Songyu Wang1School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaSchool of Information and Management Sciences, Henan Agricultural University, Zhengzhou 450046, ChinaIn this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. It is noted that in the standard backstepping design, the fractional derivative of the virtual quantity needs to be calculated repeatedly, which will lead to a sharp increase in the number of controller terms with the increase of the system dimension and finally make the control system difficult to bear. To handle the estimation error, certain robust terms in the controller at the last step are designed. The stability of the controlled system is proven strictly. In addition, the proposed controller has a simple form which can be easily implemented. Finally, in order to verify our theoretical method, the control simulation based on a fractional-order chaotic system is implemented.http://dx.doi.org/10.1155/2021/1270187 |
| spellingShingle | Youjun Chen Songyu Wang Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems Complexity |
| title | Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems |
| title_full | Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems |
| title_fullStr | Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems |
| title_full_unstemmed | Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems |
| title_short | Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems |
| title_sort | neural network backstepping controller design for fractional order nonlinear systems |
| url | http://dx.doi.org/10.1155/2021/1270187 |
| work_keys_str_mv | AT youjunchen neuralnetworkbacksteppingcontrollerdesignforfractionalordernonlinearsystems AT songyuwang neuralnetworkbacksteppingcontrollerdesignforfractionalordernonlinearsystems |