Design of sampled-data controller for T–S fuzzy system with the refined fractional delayed-state and its applications

Ramasamy Subramaniyam, Manivannan Annamalai, Young Hoon Joo
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Abstract

The paper is concerned with the development of a sampled-data (SD) controller designed for Takagi–Sugeno (T–S) fuzzy systems. A key highlight is the incorporation of a refined fractional delayed-state into this control approach. The primary aim is to establish criteria for system stabilization, thereby ensuring the asymptotic stability of the considered systems. This objective is pursued within the framework of the newly designed control methodology. The core contribution of work explains in the introduction of an innovative Lyapunov–Krasovskii functional (LKF) tailored to T–S fuzzy systems. This novel approach capitalizes on the efficacy of sampling intervals. The LKF design takes advantage of variable attributes tied to the real sampling pattern, effectively reducing the conservatism of the outcomes. Moreover, the paper introduces a sophisticated fractional delayed-state concept, which plays a pivotal role in shaping a modified looped functional-based LKF. The stability criteria are then formulated through the utilization of linear matrix inequalities (LMIs) and integral inequalities. These criteria perform dynamic part in establishing the asymptotic stability of considered systems when subjected to the designed control approach.

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具有精炼分数延迟状态的 T-S 模糊系统的采样数据控制器设计及其应用
本文关注的是为高木-菅野(T-S)模糊系统设计的采样数据(SD)控制器的开发。其中一个主要亮点是将细化的分数延迟状态纳入这种控制方法。主要目的是建立系统稳定标准,从而确保所考虑系统的渐近稳定性。这一目标是在新设计的控制方法框架内实现的。这项工作的核心贡献在于为 T-S 模糊系统引入了创新的 Lyapunov-Krasovskii 函数 (LKF)。这种新方法利用了采样间隔的功效。LKF 设计利用了与实际抽样模式相关的变量属性,有效降低了结果的保守性。此外,本文还引入了一个复杂的分数延迟状态概念,该概念在形成基于修正循环函数的 LKF 时发挥了关键作用。然后,利用线性矩阵不等式(LMI)和积分不等式制定了稳定性标准。在采用所设计的控制方法时,这些标准在建立所考虑系统的渐近稳定性方面发挥了积极作用。
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