Parameter-dependent H2 state estimation for nonlinearl systems

Abstract

The state estimation of general nonlinear systems is investigated through a parameter-dependent approach. This paper adopts the polytopic approximation for the nonlinear systems, which facilitates the application of analytical approaches for resultant convex-bounded linear systems into the given nonlinear systems. The design of a high performance H2 state estimator is firstly determined by solving a convex optimization problem constrained by relaxed linear matrix inequalities (LMIs). The tensor product (TP) model transformation is then adopted to obtain the polytopic linearization. Specifically, A new process is presented to correct the result of the TP model transformation such that a necessary condition to solve the state estimation problem is assured. Finally, a numerical simulation is performed to illustrate the design process and verify the performance.