Fault diagnosis for semilinear distributed parameter systems with actuator/sensor based on iterative learning control

Abstract

AbstractThis paper focuses on the fault diagnosis problem for a class of semilinear distributed parameter systems with actuator and sensor. To diagnose the actual fault, a fault estimator is designed by using an introduced virtual fault for this system. Based on the semigroup theory and λ‐norm, the residual signal is used in the PD‐type iterative learning control scheme to regulate the introduced virtual fault, making the virtual fault track the practical fault. Then, the goal of fault diagnosis is obtained. Finally, the effectiveness of the proposed method is tested on a Fisher equation and applied to a class of typical chemical industry processes.