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Stability Conditions for LMI-Based Fuzzy Control From Viewpoint of Membership Functions

机译:从隶属函数角度看基于LMI的模糊控制的稳定性条件

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In this paper, we investigate the stability conditions for linear matrix inequality (LMI)-based fuzzy control design. Especially, we focus on the dependence of the stability upon membership functions. In general, the membership functions in the rule bases of Takagi-Sugeno (T-S) fuzzy model and controllers are the same and restricted between 0 and 1. In contrast to this setting, we obtain some new results when different membership functions are considered and their values lying outside the interval of [0,1] are allowed. Applying Lyapunov equation and a convex hull of fuzzy subsystems, we first establish a relationship between the stable interval characteristic polynomial and a set of feasible LMIs. Then Kharitonov's theorem gives an insight for the solvability of stabilization problems using LMI-based design and, this leads that the membership functions have an influence on stability. On the other hand, the LMI condition leads to the well-known results for LMI-based fuzzy control design. We further indicate that the different LMI conditions arise due to the same or different membership functions and find their own applications on adaptive fuzzy control. Finally, if the unit interval constraint is removed, an LMI condition for global stability is obtained
机译:在本文中,我们研究了基于线性矩阵不等式(LMI)的模糊控制设计的稳定性条件。特别是,我们关注稳定性对隶属函数的依赖性。通常,Takagi-Sugeno(TS)模糊模型和控制器的规则库中的隶属函数是相同的,并且限制在0到1之间。与该设置相反,当考虑不同的隶属函数及其关系时,我们会得到一些新结果。允许在[0,1]间隔之外的值。应用Lyapunov方程和模糊子系统的凸包,我们首先建立了稳定区间特征多项式与一组可行的LMI之间的关系。然后,哈里通诺夫定理给出了使用基于LMI的设计解决稳定问题的见解,这导致隶属函数对稳定性有影响。另一方面,LMI条件导致了基于LMI的模糊控制设计的众所周知的结果。我们进一步指出,由于相同或不同的隶属函数而产生了不同的LMI条件,并在自适应模糊控制中找到了自己的应用。最后,如果删除了单位间隔约束,则可以获得全局稳定性的LMI条件

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