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

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-04-25 DOI:10.1155/2024/7126978
Farzad Soltanian, Amir Parviz Valadbeigi, Jafar Tavoosi, Rahmat Aazami, Mokhtar Shasadeghi, Mohammadamin Shirkhani, Amirreza Azizi
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引用次数: 0

Abstract

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.

基于 T-S 模糊非线性系统的自适应最优终端滑模控制
本研究利用高木-菅野模糊模型来表示非线性系统的一个子集,并提出了一种创新的动态终端滑模控制(TSMC)自适应方法。所考虑的系统包括参数和执行器中的有界不确定性,以及对外部干扰的敏感性。性能评估需要通过两个步骤设计自适应终端滑动面。首先,利用线性矩阵不等式(LMI)技术,以 H2- 性能和部分特征结构分配为基础,开发状态反馈增益和控制器。随后,利用推导出的状态反馈增益和设计的终端滑动模式(TSM)控制器,通过凸优化实现动态滑动增益。这种方法与传统方法不同,它结合了控制努力和估算致动器不确定性边界,同时还解决了滑动面和 TSM 控制器设计的复杂性。TSM 控制器被重新定义为严格的反馈形式,使其适用于解决非线性系统中的输出跟踪难题。对比仿真验证了所提出的 TSM 控制器的有效性,强调了它的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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