Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system
Abstract This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another resear...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-35307-0 |
| _version_ | 1797822911008997376 |
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| author | Qianqian Mu Fei Long Bin Li |
| author_facet | Qianqian Mu Fei Long Bin Li |
| author_sort | Qianqian Mu |
| collection | DOAJ |
| description | Abstract This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance. |
| first_indexed | 2024-03-13T10:15:16Z |
| format | Article |
| id | doaj.art-e1ff076829be44579173559cb6500e57 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T10:15:16Z |
| publishDate | 2023-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-e1ff076829be44579173559cb6500e572023-05-21T11:16:57ZengNature PortfolioScientific Reports2045-23222023-05-0113111010.1038/s41598-023-35307-0Adaptive neural network prescribed performance control for dual switching nonlinear time-delay systemQianqian Mu0Fei Long1Bin Li2College of Big Data and Information Engineering, Guizhou UniversitySchool of Artificial Intelligence and Electrical Engineering, Guizhou Institute of TechnologyChina Tower Corporation Limited Guizhou Provincial BranchAbstract This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance.https://doi.org/10.1038/s41598-023-35307-0 |
| spellingShingle | Qianqian Mu Fei Long Bin Li Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system Scientific Reports |
| title | Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system |
| title_full | Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system |
| title_fullStr | Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system |
| title_full_unstemmed | Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system |
| title_short | Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system |
| title_sort | adaptive neural network prescribed performance control for dual switching nonlinear time delay system |
| url | https://doi.org/10.1038/s41598-023-35307-0 |
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