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

被引：1

作者：

Soltanian F. ^{[1
,2
]}

Valadbeigi A.P. ^{[1
,3
]}

Tavoosi J. ^{[4
]}

Aazami R. ^{[4
]}

Shasadeghi M. ^{[2
]}

Shirkhani M. ^{[4
]}

Azizi A. ^{[5
]}

机构：

[1] Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6G 2M9, AB

[2] Electrical Engineering Faculty, Shiraz University of Technology, Shiraz

[3] Department of Electrical Engineering, Islamic Azad University, Khorramabad Branch, Khorramabad

[4] Department of Electrical Engineering, Ilam University, Ilam

[5] Department of Electrical Engineering, Shahed University of Tehran, Tehran

来源：

Complexity | 2024年 / 2024卷

关键词：

Adaptive control systems - Controllers - Convex optimization - Linear matrix inequalities - Nonlinear systems - Sliding mode control - State feedback - Uncertainty analysis;

D O I：

10.1155/2024/7126978

中图分类号：

学科分类号：

摘要：

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.

引用

共 55 条

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