Fault detection and isolation filter design for linear parameter varying systems

An ℋ_∞ 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_∞ performance; these conditions result in convex linear matrix inequalities (LMIs) that can be solved efficiently via 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 are demonstrated using a structural system simulation example, which includes a faulty actuator and external disturbances