Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems

被引：0
|
作者：
Soltanian, Farzad [1 ,2 ]
Valadbeigi, Amir Parviz [1 ,3 ]
Tavoosi, Jafar [4 ]
Aazami, Rahmat [4 ]
Shasadeghi, Mokhtar [2 ]
Shirkhani, Mohammadamin [4 ]
Azizi, Amirreza [5 ]
机构：
[1] Department of Electrical and Computer Engineering, University of Alberta, Edmonton,AB,T6G 2M9, Canada
[2] Electrical Engineering Faculty, Shiraz University of Technology, Shiraz,715555-313, Iran
[3] Department of Electrical Engineering, Islamic Azad University, Khorramabad Branch, Khorramabad, Iran
[4] Department of Electrical Engineering, Ilam University, Ilam, Iran
[5] Department of Electrical Engineering, Shahed University of Tehran, Tehran, Iran
来源：
Complexity | 2024年 / 2024卷
关键词：
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. © 2024 Farzad Soltanian et al;
D O I：
10.1155/2024/7126978
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