Membership function-dependent predictive control for interval type-2 Takagi–Sugeno fuzzy system

IF 2.7 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Asian Journal of Control Pub Date : 2023-09-12 DOI:10.1002/asjc.3216

Hua Zheng, Yuanyuan Zou, Shaoyuan Li

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Abstract

In this paper, the problem of membership function-dependent model predictive control (MFD-MPC) of interval type-2 Takagi–Sugeno (IT2 T-S) fuzzy system is investigated. An online MFD-MPC optimization problem is formulated to minimize an infinite horizon objective function subject to hard constraints on control input and system state. By using the variable dimension expansion method and dividing the operation domain of independent variables into several subdomains, a subregion-based state feedback model predictive controller that offers more design flexibility is designed to stabilize the open-loop fuzzy system. Based on descriptor system theory, the variable mismatching phenomenon between MFs and the coupling between plant, controller, and Lyapunov matrix are eliminated. Then, using the piecewise linear approximation technology, MFD sufficient conditions of low conservatism on guaranteeing recursive feasibility and the stability of IT2 closed-loop fuzzy system are deduced by tightening terminal constraint set. Finally, a numerical example is provided to further explain the advance of the proposed method.

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区间型 Takagi-Sugeno 模糊系统的成员函数相关预测控制

本文研究了区间 2 型高木-菅野（IT2 T-S）模糊系统的成员函数依赖模型预测控制（MFD-MPC）问题。提出了一个在线 MFD-MPC 优化问题，即在控制输入和系统状态的硬约束条件下，最小化无限视界目标函数。通过使用变量维数扩展方法并将自变量的操作域划分为多个子域，设计了一种基于子区域的状态反馈模型预测控制器，该控制器具有更大的设计灵活性，可稳定开环模糊系统。基于描述符系统理论，消除了中频之间的变量不匹配现象以及工厂、控制器和 Lyapunov 矩阵之间的耦合。然后，利用分片线性近似技术，通过收紧终端约束集，推导出保证 IT2 闭环模糊系统递归可行性和稳定性的低保守性 MFD 充分条件。最后，通过一个数值实例进一步说明了所提方法的先进性。

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

Asian Journal of Control 工程技术-自动化与控制系统

CiteScore

4.80

自引率

25.00%

发文量

253

审稿时长

7.2 months

期刊介绍： The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.

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