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LMI-Based Stability Analysis of Fuzzy-Model-Based Control Systems Using Approximated Polynomial Membership Functions

机译:使用近似多项式隶属函数的基于LMI的基于模糊模型的控制系统的稳定性分析

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摘要

Relaxed linear-matrix-inequality-based stability conditions for fuzzy-model-based control systems with imperfect premise matching are proposed. First, the derivative of the Lyapunov function, containing the product terms of the fuzzy model and fuzzy controller membership functions, is derived. Then, in the partitioned operating domain of the membership functions, the relations between the state variables and the mentioned product terms are represented by approximated polynomials in each subregion. Next, the stability conditions containing the information of all subsystems and the approximated polynomials are derived. In addition, the concept of the $S$-procedure is utilized to release the conservativeness caused by considering the whole operating region for approximated polynomials. It is shown that the well-known stability conditions can be special cases of the proposed stability conditions. Simulation examples are given to illustrate the validity of the proposed approach.
机译:提出了具有不完美前提匹配的基于模糊模型的控制系统的基于松弛线性矩阵不等式的稳定性条件。首先,导出Lyapunov函数的导数,其中包含模糊模型和模糊控制器隶属函数的乘积项。然后,在隶属函数的分区操作域中,状态变量与提到的乘积项之间的关系由每个子区域中的近似多项式表示。接下来,导出包含所有子系统信息和近似多项式的稳定性条件。此外,使用$ S $程序的概念来消除由于考虑了多项式的整个操作区域而引起的保守性。结果表明,众所周知的稳定性条件可以是所提出的稳定性条件的特例。仿真实例说明了该方法的有效性。

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