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Design of Polynomial Fuzzy Observer-Controller with Membership Functions using Unmeasurable Premise Variables for Nonlinear Systems

机译:基于不可测前提变量的隶属函数多项式模糊观测器-控制器的非线性系统设计

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摘要

In this paper, the stability of polynomial fuzzy-model-based (PFMB) observer-control system is investigated via Lyapunov stability theory. The polynomial fuzzy observer with unmeasurable premise variables is designed to estimate the system states. Then the estimated system states are used for the state-feedback control of nonlinear systems. Although the consideration of the polynomial fuzzy model and unmeasurable premise variables enhances the applicability of the fuzzy-model-based (FMB) control strategy, it leads to non-convex stability conditions. Therefore, the refined completing square approach is proposed to derive convex stability conditions in the form of sum of squares (SOS) with less manually designed parameters. In addition, the membership functions of the polynomial observer-controller are optimized by the improved gradient descent method, which outperforms the widely applied parallel distributed compensation (PDC) approach according to a general performance index. Simulation examples are provided to verify the proposed design and optimization scheme.
机译:本文基于李雅普诺夫稳定性理论研究了基于多项式模糊模型(PFMB)的观测器-控制系统的稳定性。具有不可测量的前提变量的多项式模糊观测器被设计为估计系统状态。然后将估计的系统状态用于非线性系统的状态反馈控制。尽管对多项式模糊模型和不可测前提变量的考虑增强了基于模糊模型(FMB)的控制策略的适用性,但这会导致非凸稳定条件。因此,提出了一种完善的完备平方方法,以较少的人工设计参数以平方和(SOS)的形式导出凸稳定条件。此外,多项式观察器-控制器的隶属函数通过改进的梯度下降法进行了优化,根据一般性能指标,该方法优于广泛应用的并行分布补偿(PDC)方法。提供了仿真示例,以验证所提出的设计和优化方案。

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