ROBUST FAULT DIAGNOSIS FOR A CLASS OF NONLINEAR DISCRETE DYNAMIC SYSTEMS BASED ON LMI

A new method of robust fault diagnosis for a class of nonlinear discrete dynamic systems with uncertainties is proposed. It can not only detect faults, but also isolate and identify faults. Firstly, it converts the problem of fault identification into a min max problem by constructing an auxiliary system, and designs the gain matrix in the auxiliary system appropriately such that the state difference equation and the output difference equation of the auxiliary system and the systems to be diagnosed are both stable, then converts the min max problem into a LMI problem, and finally realizes the fault diagnosis by solving the LMI problem. The analyses for robustness, sensitivity and error of fault identification are also considered. Simulation indicates its effectiveness.