Synthesis of robust gain scheduling based fault detection filters for a class of parameter uncertain nonlinear systems

We discuss the solution of the fault detection problem for parameter uncertain nonlinear systems using a gain scheduling based approach. By using a set of linearized plant models, a set of least order linear fault detection filters is determined to serve for interpolation based gain scheduling. The basic synthesis approach is the nullspace method for constant linear systems, whose extension to the case of linear parameter varying (LPV) models provides the methodological framework for the synthesis of robust fault detection filters. The resulting gain scheduled fault detection filter provides robustness with respect to both model nonlinearities as well as parametric uncertainties. In a general setting, we consider the case when part of the uncertain parameters are non-measurable and part of them are measurable.