Robust H2H∞ Filter Design for a Class of Nonlinear Stochastic Systems with State-Dependent Noise

Abstract EN

This paper investigates the problem of robust filter design for a class of nonlinear stochastic systems with state-dependent noise.

The state and measurement are corrupted by stochastic uncertain exogenous disturbance and the dynamic system is modeled by Itô-type stochastic differential equations.

For this class of nonlinear stochastic systems, the robust H∞ filter can be designed by solving linear matrix inequalities (LMIs).

Moreover, a mixed H2/H∞ filtering problem is also solved by minimizing the total estimation error energy when the worst-case disturbance is considered in the design procedure.

A numerical example is provided to illustrate the effectiveness of the proposed method.