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Enhanced LMI conditions for observer-based H_∞ stabilization of Lipschitz discrete-time systems

机译:Lipschitz离散系统基于观察者的H_∞稳定的增强LMI条件

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This paper deals withH∞observer-based controller design for a class of discrete-time systems with Lipschitz nonlinearities. Usually, the observer-based control synthesis for the considered class of systems leads to the feasibility of a Bilinear Matrix Inequality (BMI). Since, solving a BMI constraint has been an NP-hard optimization problem, then linearizing this constraint to get a convex one is an interesting issue because Linear Matrix Inequalities (LMIs) are easily tractable by numerical softwares (LMI Toolboxes,..). Hence, the aim of this paper is to develop a new Linear Matrix Inequality (LMI) condition, ensuring theH∞asymptotic convergence of the observer-based controller. Due to the introduction of a slack variable technique, the usual BMI problem is equivalently transformed to a more suitable one, which leads to less conservative and more general LMI condition compared to the existing methods in the literature. Conjointly to the slack variable technique, the Lipschitz property and the Young’s relation are used in a reformulated way to obtain additional decision variables in the LMI. In the aim to further relax the proposed LMI methodology, sliding windows of delayed states and measurements are included in the structures of the controller and the observer, respectively. The obtained LMI is more general and less conservative than the first one, which can be viewed as a particular solution. To show the effectiveness and superiority of the proposed methodology, some numerical examples and comparisons are provided.
机译:本文研究了一类具有Lipschitz非线性的离散时间系统的基于H∞观测器的控制器设计。通常,对于所考虑的系统类别,基于观察者的控制综合会导致双线性矩阵不等式(BMI)的可行性。由于解决BMI约束一直是NP困难的优化问题,因此线性化此约束以获取凸约束是一个有趣的问题,因为线性矩阵不等式(LMI)可以通过数字软件轻松地处理(LMI Toolboxes,..)。因此,本文的目的是开发一种新的线性矩阵不等式(LMI)条件,以确保基于观测器的控制器的H∞渐近收敛性。由于引入了松弛变量技术,通常的BMI问题被等效地转换为更合适的BMI问题,与文献中的现有方法相比,这导致保守性降低,LMI条件变得更为笼统。与松弛变量技术结合使用,Lipschitz属性和Young的关系以重新制定的方式用于在LMI中获取其他决策变量。为了进一步放松提出的LMI方法,将延迟状态和测量值的滑动窗口分别包含在控制器和观察器的结构中。与第一个LMI相比,所获得的LMI更为通用且不那么保守,可以将其视为特定解决方案。为了显示所提出方法的有效性和优越性,提供了一些数值示例和比较。

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