A simple approach to direct LPV filter design from data for nonlinear systems

Abstract

A simple approach to the design of Linear Parameter Varying (LPV) filters for nonlinear systems is proposed. The approach relies on individuating several working conditions of the system. For each of these conditions, an almost optimal Linear Time Invariant (LTI) filter is directly identified from data. The designed LTI filters are then suitably combined to give an LPV filter. The identification of a nonlinear model and the design of a nonlinear filter are thus avoided. The direct filter design approach is applied to a problem involving real data, regarding the estimation of vehicles yaw rate.