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Adaptive sensor and actuator fault estimation for a class of uncertain Lipschitz nonlinear systems

机译:一类不确定Lipschitz非线性系统的自适应传感器和执行器故障估计

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This paper deals with state and fault estimations for a class of uncertain Lipschitz nonlinear systems. The proposed scheme combines a descriptor form observer and an adaptive sliding mode observer. The adaptive descriptor sliding approach is proposed to jointly estimate the state and reconstruct the sensor fault while rejecting the effect of uncertainties and Lipschitz nonlinearities. Using a Lyapunov analysis, the stability condition is analyzed and the observer gains are designed such that the reduced-order system is practically stable. Then, an adaptive super-twisting observer is derived to reconstruct the actuator faults. The main feature of the proposed adaptive scheme is that it does not overestimate the observer gains, which mitigates chattering in the presence of bounded uncertainties, actuator, and sensor faults with unknown boundaries. Simulation results for a robotic manipulator show the effectiveness of the proposed method. Copyright (c) 2015John Wiley & Sons, Ltd.
机译:本文涉及一类不确定的Lipschitz非线性系统的状态和故障估计。所提出的方案结合了描述符形式观察器和自适应滑模观察器。提出了一种自适应描述子滑动方法,可以在不考虑不确定性和Lipschitz非线性影响的情况下,共同估计状态并重建传感器故障。使用李雅普诺夫(Lyapunov)分析,分析了稳定性条件,并设计了观测器增益,以使降阶系统实际上稳定。然后,导出自适应超扭曲观测器以重建致动器故障。所提出的自适应方案的主要特点是它不会高估观察者的增益,从而在存在不确定边界,致动器和边界未知的传感器故障的情况下减轻了颤动。机器人操纵器的仿真结果表明了该方法的有效性。版权所有(c)2015 John Wiley&Sons,Ltd.

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