Fault detection and estimation for discrete-time switched systems

In this paper, a novel fault detection and estimation method is proposed for discrete-time switched systems. In the proposed design, a fault detection observer with online learning capability is utilized to generate a residual which is obtained by comparing the system output with respect to the observer output. A fault is successfully detected if the generated residual exceeds an a priori chosen threshold. Subsequently, the fault magnitude is estimated online by using a suitable parameter update law.