Fault detection and isolation filter design for linear parameter varying systems

An H-infinity approach to design a fault detection and isolation gain scheduled filter for linear parameter varying (LPV) systems is presented in this paper. The system matrices are assumed to depend affinely on real-time measured varying parameters. Solvability conditions are derived using the quadratic H-infinity performance; these conditions result in convex linear matrix inequalities (LMIs) that can be solved efficiently via recently developed optimization techniques. The designed filter is parameter varying and consequently scheduled along the varying parameters' trajectories. The fault detection and isolation is accomplished by estimating the input fault signal vector, and a reference model is used in order to shape the desired performance of the filter. Finally, the methods axe demonstrated using a structural system simulation example, which includes a faulty actuator and external disturbances.