Output-feedback sampled-data control for uncertain nonlinear system

H. Sung, Jin Bae Park, Jong-Seon Kim, Y. Joo
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Abstract

In this paper, we concern an intelligent digital re-design(IDR) method for a fuzzy observer-based output-feedback control system which includes parametric uncertainties. The term IDR is to convert an existing analog control into an equivalent digital counterpart via state-matching. The considered IDR problem is viewed as convex minimization problem of the norm distances between linear operators to be matched and its constructive condition is formulated in terms of linear matrix inequalities (LMIs). The main features of the proposed method are that the state estimation error in the plant dynamics is considered in the IDR condition that plays a crucial role in the performance improvement; the uncertainties in the plant dynamics is shown in the IDR condition by virtue of the bilinear and inverse-bilinear approximation method; finally, the stability property is preserved by the proposed IDR method.
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不确定非线性系统的输出反馈采样数据控制
本文研究了包含参数不确定性的基于模糊观测器的输出反馈控制系统的智能数字再设计(IDR)方法。术语IDR是通过状态匹配将现有的模拟控制转换为等效的数字控制。将所考虑的IDR问题视为待匹配线性算子范数距离的凸极小化问题,并将其构造条件用线性矩阵不等式的形式表述出来。该方法的主要特点是在IDR条件下考虑了系统动力学中的状态估计误差,这对系统性能的提高起着至关重要的作用;利用双线性和反双线性逼近方法,在IDR条件下显示了植物动力学中的不确定性;最后,该方法保持了系统的稳定性。
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