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Design of Unknown Inputs Observer for a Class of Discrete-Time Takagi-Sugeno Descriptor Models

机译:一类离散Takagi-Sugeno描述符模型的未知输入观测器的设计

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This paper addresses the problem of simultaneous estimation of unmeasurable states and unknown inputs (UIs) for a class of discrete-time nonlinear descriptor models (DNDMs) described by Takagi-Sugeno (T-S) structure with unmeasurable premise variables. The UIs affect both state and output of the system. The main idea of the proposed design of fuzzy unknown inputs observer (FUIO) is based on the separation between dynamic and static relations in T-S descriptor model. First, the method permitting to separate dynamic equations from static equations is developed. Next, based on the augmented fuzzy model which contains the dynamic equations and the UIs, a new FUIO design in explicit structure is given. The exponential convergence of the state estimation error is studied by using the Lyapunov theory and the stability conditions are given in terms of linear matrix inequalities (LMIs). Finally, an application to a DNDM of a single-link flexible joint robot is presented in order to illustrate the validity and applicability of the proposed method.
机译:本文针对由高木-Sugeno(T-S)结构描述的具有不可测前提变量的一类离散时间非线性描述符模型(DNDM),解决了同时估计不可测状态和未知输入(UI)的问题。 UI会影响系统的状态和输出。提出的模糊未知输入观测器(FUIO)设计的主要思想是基于T-S描述符模型中动态和静态关系的分离。首先,开发了允许将动态方程式与静态方程式分离的方法。接下来,基于包含动态方程和用户界面的增强模糊模型,给出了一种显式结构的新FUIO设计。利用李雅普诺夫理论研究状态估计误差的指数收敛性,并根据线性矩阵不等式(LMI)给出稳定性条件。最后,提出了一种应用于单链柔性关节机器人的DNDM的方法,以说明该方法的有效性和适用性。

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