不完全匹配条件下模糊模型控制系统的稳定性分析与性能设计

H. Lam, C. Yeung, F. Leung
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引用次数: 13

摘要

本文介绍了非线性系统的稳定性分析和性能设计。采用T-S模糊模型来表示非线性对象,便于进行稳定性分析。在T-S模糊模型与模糊控制器不具有相同隶属函数的不完全匹配前提下,提出了一种模糊控制器来完成控制任务。因此,可以提高设计的灵活性,并可以采用简单的隶属函数来降低模糊控制器的结构复杂性。然而,由完美的前提匹配所给予的有利特性将会消失,从而导致保守的稳定条件。本文在不完全前提匹配的情况下,考虑了模糊模型和控制器的隶属函数信息。采用基于lyapunov的方法,导出了基于lmi的稳定性条件,以保证系统的稳定性。为了减轻稳定性条件的保守性,引入自由矩阵。为保证系统的性能,推导了基于lmi的性能条件。仿真实例说明了该方法的有效性。
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Stability Analysis and Performance Deign for Fuzzy-Model-Based Control System under Imperfect Premise Matching
This paper presents the stability analysis and performance design for nonlinear systems. The T-S fuzzy model is employed to represent the nonlinear plant to facilitate the stability analysis. A fuzzy controller, under imperfect premise matching such that the T-S fuzzy model and the fuzzy controller do not share the same membership functions, is proposed to perform the control task. Consequently, the design flexibility can be enhanced and simple membership functions can be employed to lower the structural complexity of the fuzzy controller. However, the favourable characteristic given by perfect premise matching will vanish, which leads to conservative stability conditions. In this paper, under imperfect premise matching, the information of membership functions of the fuzzy model and controller is considered during the stability analysis. LMI-based stability conditions are derived to guarantee the system stability using the Lyapunov-based approach. Free matrices are introduced to alleviate the conservativeness of the stability conditions. LMI-based performance conditions are also derived to guarantee the system performance. Simulation examples are given to illustrate the effectiveness of the proposed approach.
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