A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems
A new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters. Fourier series expansion (FSE) is introduced to deal with the problem of uncertain...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Physics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2023.1127884/full |
| _version_ | 1811175398633897984 |
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| author | Chunli Zhang Lei Yan Yangjie Gao Wenqing Wang Keming Li Duo Wang Long Zhang |
| author_facet | Chunli Zhang Lei Yan Yangjie Gao Wenqing Wang Keming Li Duo Wang Long Zhang |
| author_sort | Chunli Zhang |
| collection | DOAJ |
| description | A new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters. Fourier series expansion (FSE) is introduced to deal with the problem of uncertain time-varying parameters. The bound of the expanded remaining items is unknown. A typical convergent series is used to deal with the unknown bound in the design process of the controller. The adaptive iterative learning synchronization controller and parameter update laws are designed. Two different chaotic systems are synchronized asymptotically according to different proportional functions on a finite time interval by Lyapunov stability analysis. The simulation example proves the feasibility and effectiveness of the proposed method. |
| first_indexed | 2024-04-10T19:36:32Z |
| format | Article |
| id | doaj.art-5ac1fd4bcb1a4bf89788df0cad27ea5d |
| institution | Directory Open Access Journal |
| issn | 2296-424X |
| language | English |
| last_indexed | 2024-04-10T19:36:32Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physics |
| spelling | doaj.art-5ac1fd4bcb1a4bf89788df0cad27ea5d2023-01-30T05:28:09ZengFrontiers Media S.A.Frontiers in Physics2296-424X2023-01-011110.3389/fphy.2023.11278841127884A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systemsChunli Zhang0Lei Yan1Yangjie Gao2Wenqing Wang3Keming Li4Duo Wang5Long Zhang6Xi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an, ChinaXi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an, ChinaXi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an, ChinaXi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an, ChinaState Grid Xi’an Electric Power Supply Company, Xi’an, ChinaState Grid Xi’an Electric Power Supply Company, Xi’an, ChinaState Grid Xi’an Electric Power Supply Company, Xi’an, ChinaA new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters. Fourier series expansion (FSE) is introduced to deal with the problem of uncertain time-varying parameters. The bound of the expanded remaining items is unknown. A typical convergent series is used to deal with the unknown bound in the design process of the controller. The adaptive iterative learning synchronization controller and parameter update laws are designed. Two different chaotic systems are synchronized asymptotically according to different proportional functions on a finite time interval by Lyapunov stability analysis. The simulation example proves the feasibility and effectiveness of the proposed method.https://www.frontiersin.org/articles/10.3389/fphy.2023.1127884/fullhybrid function projective synchronizationchaotic systemsadaptive iterative learning controlFourier series expansionfinite time |
| spellingShingle | Chunli Zhang Lei Yan Yangjie Gao Wenqing Wang Keming Li Duo Wang Long Zhang A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems Frontiers in Physics hybrid function projective synchronization chaotic systems adaptive iterative learning control Fourier series expansion finite time |
| title | A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems |
| title_full | A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems |
| title_fullStr | A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems |
| title_full_unstemmed | A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems |
| title_short | A new adaptive iterative learning control of finite-time hybrid function projective synchronization for unknown time-varying chaotic systems |
| title_sort | new adaptive iterative learning control of finite time hybrid function projective synchronization for unknown time varying chaotic systems |
| topic | hybrid function projective synchronization chaotic systems adaptive iterative learning control Fourier series expansion finite time |
| url | https://www.frontiersin.org/articles/10.3389/fphy.2023.1127884/full |
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