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Stabilization of Markovian jump systems with incomplete knowledge of transition probabilities and input quantization

机译:具有不完全的转移概率和输入量化知识的马尔可夫跳跃系统的镇定

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摘要

This paper introduces the stabilization condition for the Markovian jump systems (MJSs) with incomplete knowledge of transition probabilities and input quantization. To obtain the less conservative stabilization condition, an appropriate weighting method is proposed by using all possible slack variables from the relationship of the transition probabilities, which does lead to a form of linear matrix inequalities (LMIs). Further, a proposed controller not only stabilizes the MJS with incomplete knowledge of transition probabilities but also eliminates the effect of input quantization. Simulation examples report the effectiveness of the proposed criterion. (C) 2015 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:本文介绍了对转移概率和输入量化知识不完全的马尔可夫跳跃系统(MJS)的稳定条件。为了获得较不保守的稳定条件,从过渡概率的关系中使用所有可能的松弛变量,提出了一种合适的加权方法,这确实导致了线性矩阵不等式(LMI)的形式。此外,所提出的控制器不仅利用不完全的转移概率知识来稳定MJS,而且消除了输入量化的影响。仿真示例报告了所提出标准的有效性。 (C)2015富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2015年第10期|4354-4365|共12页
  • 作者单位

    Pohang Univ Sci & Technol, Div Elect Engn, Pohang 790784, South Korea.;

    Pohang Univ Sci & Technol, Div Elect Engn, Pohang 790784, South Korea.;

    Pohang Univ Sci & Technol, Div Elect Engn, Pohang 790784, South Korea.;

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  • 入库时间 2022-08-18 02:57:48

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