基于模糊模型的非线性分组网络控制系统镇定

The 27th Chinese Control and Decision Conference (2015 CCDC) Pub Date : 2015-07-20 DOI:10.1109/CCDC.2015.7162285

B. Tang, Jiali Qin, Yun Zhang

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引用次数: 0

摘要

本文研究了基于时滞分布方法的时变传输时延和传输间隔非线性分组网络控制系统的模糊模型镇定问题。将输入延迟的实时分布建模为一个相互依赖的非同分布过程。提出了一种具有多输入延迟子系统的随机切换Takagi-Sugeno模糊系统来对非线性分组ncs进行建模。基于改进的Lyapunov-Krasovskii方法，导出了整体系统确定性渐近稳定的新的时滞分布相关充分条件。由此产生的控制器设计方法可以表述为具有LMI约束的迭代线性优化算法。数值算例证明了本文结果的优越性。

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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Fuzzy-model-based stabilization of nonlinear packetized networked control systems

This paper is concerned with fuzzy-model-based stabilization of nonlinear packetized networked control systems (NCSs) with time-varying transmission delays and transmission intervals based on a delay-distribution approach. The real-time distribution of input delays is modeled as a dependent and nonidentically distributed process. A randomly switched Takagi-Sugeno fuzzy system with multiple input-delay subsystems is proposed to model the nonlinear packetized NCSs. Based on an improved Lyapunov-Krasovskii method, new delay-distribution-dependent sufficient conditions are derived for the deterministic asymptotical stability of the overall systems. The resulting controller design method can be formulated as an iterative linear optimization algorithm with LMI constraints. Numerical examples are presented to substantiate the advantage of our results.

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The 27th Chinese Control and Decision Conference (2015 CCDC)

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