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Neural-Network-Based Adaptive DSC Design for Switched Fractional-Order Nonlinear Systems
Sui, Shuai1,2; Chen, C. L.Philip3,4,5; Tong, Shaocheng1,6
2021-10-01
Source PublicationIEEE Transactions on Neural Networks and Learning Systems
ISSN2162-237X
Volume32Issue:10Pages:4703-4712
Abstract

Due to the particularity of the fractional-order derivative definition, the fractional-order control design is more complicated and difficult than the integer-order control design, and it has more practical significance. Therefore, in this article, a novel adaptive switching dynamic surface control (DSC) strategy is first presented for fractional-order nonlinear systems in the nonstrict feedback form with unknown dead zones and arbitrary switchings. In order to avoid the problem of computational complexity and to continuously obtain fractional derivatives for virtual control, the fractional-order DSC technique is applied. The virtual control law, dead-zone input, and the fractional-order adaptive laws are designed based on the fractional-order Lyapunov stability criterion. By combining the universal approximation of neural networks (NNs) and the compensation technique of unknown dead-zones, and stability theory of common Lyapunov function, an adaptive switching DSC controller is developed to ensure the stability of switched fractional-order systems in the presence of unknown dead-zone and arbitrary switchings. Finally, the validity and superiority of the proposed control method are tested by applying chaos suppression of fractional power systems and a numerical example.

KeywordAdaptive Control Dynamic Surface Control (Dsc) Fractional-order Filter Fractional-order Systems Nonstrict Feedback Switched Systems Unknown Dead Zone
DOI10.1109/TNNLS.2020.3027339
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science ; Engineering
WOS IDWOS:000704111000037
Scopus ID2-s2.0-85117239935
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Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorChen, C. L.Philip
Affiliation1.College of Science, Liaoning University of Technology, Jinzhou, 121001, China
2.Department of Computer and Information Science, University of Macau, Macao
3.School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510641, China
4.Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, 710072, China
5.Faculty of Science and Technology, University of Macau, 99999, Macao
6.Navigation College, Dalian Maritime University, Dalian, 116026, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Sui, Shuai,Chen, C. L.Philip,Tong, Shaocheng. Neural-Network-Based Adaptive DSC Design for Switched Fractional-Order Nonlinear Systems[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(10), 4703-4712.
APA Sui, Shuai., Chen, C. L.Philip., & Tong, Shaocheng (2021). Neural-Network-Based Adaptive DSC Design for Switched Fractional-Order Nonlinear Systems. IEEE Transactions on Neural Networks and Learning Systems, 32(10), 4703-4712.
MLA Sui, Shuai,et al."Neural-Network-Based Adaptive DSC Design for Switched Fractional-Order Nonlinear Systems".IEEE Transactions on Neural Networks and Learning Systems 32.10(2021):4703-4712.
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