Robust fault detection and adaptive parameter identification for DC-DC converters via switched systems

In this paper, the problem of fault detection and identification for DC-DC converters is presented. First, switched systems model and fault model are analyzed based the switched characteristics of the DC-DC converters, taking the DC-DC buck converter as an example. According to the switched Lyapunov function technique, a fault detection observer and a bank of linear switched fault identification observers are designed for the switched systems. Next, the fault detection observer detects the fault based on the residual produced by the observer output and actual output. After the fault is detected, fault identification observers are activated. The location of fault is identified by comparing the residual evaluation functions. Meanwhile, the adaptive parameter identification is achieved by choosing an appropriate adaptive law. Finally, in order to show the feasibility of the fault detection and identification, the simulation results are given in this article.