基于滑模变结构的火炮位置伺服系统故障诊断

Fault Diagnosis Based on Sliding Mode Variable Structure for An Artillery Position Servo System

针对一类非线性系统,并考虑含有不知其上下界的未知输入扰动,提出了一种故障诊断方案.利用滑模变结构中的等值控制方法设计了滑模状态观测器;利用自适应方法实现了对故障的重构;采用Lyapunov方法对观测器和故障重构的收敛性进行了证明.为减少滑模运动的抖动,设计了一个模糊神经网络对观测器参数实时调整,并给出网络的学习算法.将本文提出的方法在火炮伺服系统中应用,证明了该方法的有效性.

A fault diagnosis proposal for a class of nonlinear system has been presented in this paper. The studied uncertain nonlinear system is subject to input disturbance with unknown bound. First, two observers were designed for fault reconstruction. One of them was a sliding mode observer which was designed by means of specific equivalent control methodology. On the basis of that, another adaptive observer was designed to carry out reconstruction of fault. The convergence of both of them was proved by means of Lyapunov method. Second, in order to reduce the chattering of sliding mode motion, a design of fuzzy neural network and its learning algorithm was proposed to on-line adjust the related parameters. Finally, the results of some numerical simulations on an artillery position servo system verify the validity of the proposed approaches.