Observer-based Fault-Tolerant Control of an Electro-Hydraulic Actuator with mismatched disturbance

V. Phan, K. Ahn
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引用次数: 3

Abstract

This article develops a novel fault-tolerant controller for an electro-hydraulic actuation system in the presence of mismatched disturbance and sensor malfunction. In detail, on the basic of the linear matrix inequality (LMI) approach, a nonlinear unknown input observer (NUIO) is designed to simultaneously estimate the sensor fault and output of position that is not impacted by the external disturbance. Next, a fault detection module is constructed to detect sensor fault and feedback the estimated position to the controller when the fault occurs. For the purpose of approximating and reducing the influence of the mismatched disturbance, a radial basis function neural network (RBFNN) is deployed. The combination of NUIO, RBFNN in a dynamic surface control (DSC) approach is introduced to not only achieve precision tracking control but also guarantee a stable system in the event of sensor fault. Furthermore, the Lyapunov function method is utilized to analyze the stability of the resulting closed-loop system. Finally, simulation results and comparison studies are presented to verify the effectiveness and feasibility of the theoretical claims.
不匹配扰动下电液作动器的观测器容错控制
针对电液作动系统存在不匹配干扰和传感器故障的情况,设计了一种新型的容错控制器。在线性矩阵不等式(LMI)方法的基础上,设计了一个非线性未知输入观测器(NUIO),用于同时估计传感器故障和不受外界干扰影响的位置输出。其次,构造故障检测模块,检测传感器故障,并在故障发生时将估计位置反馈给控制器。为了逼近和减小失配扰动的影响,采用径向基函数神经网络(RBFNN)。在动态面控制(DSC)方法中引入NUIO和RBFNN相结合的方法,既能实现精确的跟踪控制,又能在传感器发生故障时保证系统的稳定。此外,利用李雅普诺夫函数法分析了闭环系统的稳定性。最后给出了仿真结果和对比研究,验证了理论主张的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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