Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems
This study utilizes the Takagi–Sugeno fuzzy model to represent a subset of nonlinear systems and presents an innovative adaptive approach for optimal dynamic terminal sliding mode control (TSMC). The systems under consideration encompass bounded uncertainties in parameters and actuators, as well as...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2024/7126978 |
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| _version_ | 1832553114188644352 |
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| author | Farzad Soltanian Amir Parviz Valadbeigi Jafar Tavoosi Rahmat Aazami Mokhtar Shasadeghi Mohammadamin Shirkhani Amirreza Azizi |
| author_facet | Farzad Soltanian Amir Parviz Valadbeigi Jafar Tavoosi Rahmat Aazami Mokhtar Shasadeghi Mohammadamin Shirkhani Amirreza Azizi |
| author_sort | Farzad Soltanian |
| collection | DOAJ |
| description | This study utilizes the Takagi–Sugeno fuzzy model to represent a subset of nonlinear systems and presents an innovative adaptive approach for optimal dynamic terminal sliding mode control (TSMC). The systems under consideration encompass bounded uncertainties in parameters and actuators, as well as susceptibility to external disturbances. Performance evaluation entails the design of an adaptive terminal sliding surface through a two-step process. Initially, a state feedback gain and controller are developed using Linear Matrix Inequality (LMI) techniques, grounded on H2-performance and partial eigenstructure assignment. Dynamic sliding gain is subsequently attained via convex optimization, leveraging the derived state feedback gain and the designed terminal sliding mode (TSM) controller. This approach diverges from conventional methods by incorporating control effort and estimating actuator uncertainty bounds, while also addressing sliding surface and TSM controller design intricacies. The TSM controller is redefined into a strict feedback form, rendering it suitable for addressing output-tracking challenges in nonlinear systems. Comparative simulations validate the effectiveness of the proposed TSM controller, emphasizing its practical applicability. |
| format | Article |
| id | doaj-art-40b95fdd2b414c2983bb743efc197b4b |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-40b95fdd2b414c2983bb743efc197b4b2025-02-03T05:55:21ZengWileyComplexity1099-05262024-01-01202410.1155/2024/7126978Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear SystemsFarzad Soltanian0Amir Parviz Valadbeigi1Jafar Tavoosi2Rahmat Aazami3Mokhtar Shasadeghi4Mohammadamin Shirkhani5Amirreza Azizi6Department of Electrical and Computer EngineeringDepartment of Electrical and Computer EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringElectrical Engineering FacultyDepartment of Electrical EngineeringDepartment of Electrical EngineeringThis study utilizes the Takagi–Sugeno fuzzy model to represent a subset of nonlinear systems and presents an innovative adaptive approach for optimal dynamic terminal sliding mode control (TSMC). The systems under consideration encompass bounded uncertainties in parameters and actuators, as well as susceptibility to external disturbances. Performance evaluation entails the design of an adaptive terminal sliding surface through a two-step process. Initially, a state feedback gain and controller are developed using Linear Matrix Inequality (LMI) techniques, grounded on H2-performance and partial eigenstructure assignment. Dynamic sliding gain is subsequently attained via convex optimization, leveraging the derived state feedback gain and the designed terminal sliding mode (TSM) controller. This approach diverges from conventional methods by incorporating control effort and estimating actuator uncertainty bounds, while also addressing sliding surface and TSM controller design intricacies. The TSM controller is redefined into a strict feedback form, rendering it suitable for addressing output-tracking challenges in nonlinear systems. Comparative simulations validate the effectiveness of the proposed TSM controller, emphasizing its practical applicability.http://dx.doi.org/10.1155/2024/7126978 |
| spellingShingle | Farzad Soltanian Amir Parviz Valadbeigi Jafar Tavoosi Rahmat Aazami Mokhtar Shasadeghi Mohammadamin Shirkhani Amirreza Azizi Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems Complexity |
| title | Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems |
| title_full | Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems |
| title_fullStr | Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems |
| title_full_unstemmed | Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems |
| title_short | Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems |
| title_sort | adaptive optimal terminal sliding mode control for t s fuzzy based nonlinear systems |
| url | http://dx.doi.org/10.1155/2024/7126978 |
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