Class method of fault accommodation based on inverse systemiterative learning observer
基于逆系统迭代学习观测器的故障调节方法

This paper proposed a designing method of fault accommodation based on iterative learning observer and combined both inverse system method and internal model control for a class of multi-input multi-output nonlinear invertible systems which satisfy Lipschitz conditions with actuator failure problem. Introducing a PD-type learning strategy, it designed an iterative learning observer to estimate the actuator fault rapidly and exactly. Then provided fault estimate for compensating inverse system model to keep the nonlinear system plant connected by inverse model pseudo-linearization, and, combined internal model control to carry fault tolerant control of the pseudo-linearization system. Finally, simulation results show the effectiveness of the scheme.