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State and fault estimation of a class of nonlinear systems with slow internal dynamics: Asymptotic Decoupling approach

机译:具有慢速内部动态的一类非线性系统的状态和故障估计:渐近解耦方法

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This paper presents an Unknown Input Observer (UIO) for a class of Lipschitz nonlinear systems affected by disturbances/faults and having slow internal dynamics after the decoupling of the Unknown Input (UI). Thanks to the Asymptotic Decoupling notion, the constraint related to the internal dynamics is bypassed. The nonlinear UIO presents time varying dynamics that allows to obtain the Asymptotic Decoupling notion. It will be shown that the proposed approach allows to enhance the convergence rate of the UIO. The convergence enhancement of the state estimation error is demonstrated via a Lyapunov analysis and the established conditions are expressed in terms of Linear Matrix Inequalities. Finally, simulations will be given in order to illustrate the proposed approach with some comparisons to existing techniques.
机译:本文介绍了一类受扰动/故障影响的一类Lipschitz非线性系统的未知输入观察者(UIO),并且在未知输入(UI)的解耦后具有慢的内部动态。 由于渐近解耦概念,绕过与内部动态相关的约束。 非线性UIO呈现时间变化的动态,允许获得渐变分离概念。 将表明,该方法允许提高UIO的收敛速度。 通过Lyapunov分析证明了状态估计误差的收敛增强,并且在线性矩阵不等式表达了建立的条件。 最后,将给出模拟,以说明所提出的方法与现有技术的一些比较。

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