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Model-Based Control and Stability Analysis of Discrete-Time Polynomial Fuzzy Systems With Time Delay and Positivity Constraints

机译:时滞和正约束的离散多项式模糊系统的基于模型的控制和稳定性分析

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This paper proposes a novel Lyapunov stabilization analysis of discrete-time polynomial-fuzzy-model-based control systems with time delay under positivity constraint. The polynomial fuzzy model is constructed to describe the dynamics of a nonlinear discrete-time system with time delay. A model-based polynomial fuzzy controller is designed using nonparallel distributed compensation technique to stabilize the system while driving the system states to positive using the positivity constraints. The Lyapunov stability and positivity conditions are formulated as sum-of squares. To relax the conservativeness of the obtained stability results, two main methods are proposed in this paper: first, the piecewise linear membership functions (PLMFs) are used to introduce the approximate error between piecewise and the original membership functions into the stability analysis; and second, introduce the boundary information of the premise variables into the stability analysis since the premise variables hold rich nonlinearity information. A numerical example is given to demonstrate the effectiveness of the proposed approach.
机译:本文提出了一种在正约束条件下具有时滞的离散时间多项式模糊模型控制系统的新型Lyapunov稳定性分析。构造多项式模糊模型来描述具有时滞的非线性离散时间系统的动力学。使用非并行分布补偿技术设计了基于模型的多项式模糊控制器,以使用正约束将系统状态驱动为正值时稳定系统。 Lyapunov稳定性和阳性条件公式为平方和。为了放松获得的稳定性结果的保守性,本文提出了两种主要方法:首先,使用分段线性隶属度函数(PLMF)将分段和原始隶属度函数之间的近似误差引入稳定性分析;其次,由于前提变量具有丰富的非线性信息,因此将前提变量的边界信息引入稳定性分析。数值例子说明了该方法的有效性。

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