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Stability analysis for a general class of discrete-time polynomial fuzzy dynamic systems

机译:一类一般的离散时间多项式模糊动力系统的稳定性分析

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The polynomial fuzzy models are capable of modeling complex dynamic systems. They have attracted increasing attention in the recent years as the models of choice for the development of more advanced fuzzy controllers. Little effort has been made to study the models themselves though. Like many other types of models, a polynomial fuzzy model aims at describing the physical system's dynamics based on the measured input-output data of the system. Importantly, a polynomial fuzzy model that appears to mimic the measured data reasonably well does not guarantee its validity. One way to assess model's quality is to check whether its stability is consistent with that of the physical system, which is the theme of our investigation. In this paper, we first propose a type of discrete-time polynomial fuzzy dynamic models, which comprises the general Takagi-Sugeno (T-S) fuzzy model as a special case. Then, based on the Lyapunov's linearization method, a necessary and sufficient condition is established for analytically determining the local asymptotic stability of the proposed models. A numerical example is given to illustrate the effectiveness and utility of our method.
机译:多项式模糊模型能够对复杂的动态系统进行建模。近年来,作为开发更高级的模糊控制器的首选模型,它们引起了越来越多的关注。但是,几乎没有人努力研究模型本身。像许多其他类型的模型一样,多项式模糊模型旨在基于测得的系统输入输出数据来描述物理系统的动力学。重要的是,似乎可以很好地模拟测量数据的多项式模糊模型不能保证其有效性。评估模型质量的一种方法是检查其稳定性是否与物理系统的稳定性一致,这是我们研究的主题。在本文中,我们首先提出了一种离散时间多项式模糊动态模型,其中包括一般的Takagi-Sugeno(T-S)模糊模型作为特例。然后,基于李雅普诺夫线性化方法,为分析确定所提出模型的局部渐近稳定性建立了充要条件。数值例子说明了该方法的有效性和实用性。

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