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Sampled-Data Fuzzy Control of Chaotic Systems Based on a T–S Fuzzy Model

机译:基于TS模糊模型的混沌系统采样数据模糊控制

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In this paper, a sampled-data fuzzy controller is designed to stabilize a class of chaotic systems. A Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic systems. Based on this general model, the exponential stability issue of the closed-loop systems with an input constraint is first investigated by a novel time-dependent Lyapunov functional, which is positive definite at sampling times but not necessary between the sampling times. Then, two sufficient conditions are developed for sampled-data fuzzy controller synthesis of the underlying T-S fuzzy model with or without input constraint. All the proposed results in this paper depend on both the upper and lower bounds on a sampling interval, and the available information about the actual sampling pattern is fully utilized. The proposed sampled-data fuzzy control scheme is successfully applied to the chaotic Lorenz system, which is shown to be effective and less conservative compared with existing results.
机译:本文设计了一种采样数据模糊控制器来稳定一类混沌系统。 Takagi-Sugeno(T-S)模糊模型用于表示混沌系统。在此通用模型的基础上,首先通过新颖的时间相关Lyapunov函数研究具有输入约束的闭环系统的指数稳定性问题,该函数在采样时间为正定,但在采样时间之间不是必需的。然后,为有或没有输入约束的基础T-S模糊模型的采样数据模糊控制器综合开发了两个充分条件。本文提出的所有结果均取决于采样间隔的上限和下限,并且充分利用了有关实际采样模式的可用信息。所提出的采样数据模糊控制方案已成功地应用于混沌Lorenz系统,与现有结果相比,该方法被证明是有效的,并且不那么保守。

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