Adaptive Neural Network Fault Tolerant Control for a Hydraulic System

Bohao Li, Dong Cheng, Xiaorui Zong, Haijie Jia
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Abstract

An adaptive control allocation method based on RBF neural network is proposed for a class of hydraulic systems. The goal of this method is to eliminate the output error. Firstly, the actuator fault model of hydraulic systems is established based on the Lyapunov stability principle, an improved adaptive neural network fault-tolerant controller is designed. The simulation results show that the controller has better control performance in the case of partial or combined faults in hydraulic system, can quickly implement fault-tolerant control.
液压系统的自适应神经网络容错控制
针对一类液压系统,提出了一种基于RBF神经网络的自适应控制分配方法。该方法的目标是消除输出误差。首先,基于李雅普诺夫稳定性原理建立液压系统执行器故障模型,设计改进的自适应神经网络容错控制器;仿真结果表明,该控制器在液压系统局部或组合故障情况下具有较好的控制性能,能够快速实现容错控制。
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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