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Filtering for polynomial fuzzy systems using polynomial approximated membership functions

机译:使用多项式逼近隶属度函数对多项式模糊系统进行滤波

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This paper investigates the filtering problem of polynomial fuzzy-model-based (PFMB) nonlinear systems. A novel polynomial fuzzy filter is designed to guarantee that the filter error system is asymptotically stable and satisfies a desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions represented as sum of squares (SOS), which can be solved by SOSTOOLS, are obtained based on a polynomial Lyapunov function. A numerical example is provided to demonstrate the effectiveness of the proposed method.
机译:本文研究了基于多项式模糊模型(PFMB)的非线性系统的滤波问题。设计了一种新颖的多项式模糊滤波器,以确保滤波器误差系统渐近稳定并满足期望的性能。通过泰勒级数获得的多项式近似隶属函数用于滤波分析。此外,基于多项式李雅普诺夫函数获得了足够的以平方和(SOS)表示的条件,可以通过SOSTOOLS求解。数值例子说明了所提方法的有效性。

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