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首页> 外文期刊>International Journal of Control, Automation, and Systems >Fault Estimation for T-S Fuzzy Markovian Jumping Systems based on the Adaptive Observer
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Fault Estimation for T-S Fuzzy Markovian Jumping Systems based on the Adaptive Observer

机译:基于自适应观测器的T-S模糊马尔可夫跳跃系统故障估计

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摘要

The adaptive fault estimation problem is studied for a class of stochastic Markovian jumping systems (MJSs) with time delays and nonlinear parameters. By means of Takagi-Sugeno fuzzy models, the dynamics of observer error generator and the fuzzy error dynamical system are constructed. Based on the selected Lyapunov-Krasovskii functional framework, the adaptive fault estimation algorithm is proposed to enhance the rapidity and accuracy performance of fault estimation. In terms of linear matrix inequalities techniques, a sufficient condition on the existence of the adaptive observer is presented and proved. Moreover, the presented results are also extended to multiple time-delayed non-linear MJSs. A numerical example is given at last to illustrate the effectiveness of the proposed approach.
机译:研究了一类具有时滞和非线性参数的随机马尔可夫跳跃系统(MJSs)的自适应故障估计问题。利用Takagi-Sugeno模糊模型,建立了观测器误差产生器的动力学和模糊误差动力学系统。基于所选的Lyapunov-Krasovskii功能框架,提出了一种自适应故障估计算法,以提高故障估计的速度和准确性。根据线性矩阵不等式技术,提出并证明了自适应观测器存在的充分条件。此外,提出的结果还扩展到多个时滞非线性MJS。最后给出一个数值例子来说明所提方法的有效性。

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