RobustH2/H∞Filter Design for a Class of Nonlinear Stochastic Systems with State-Dependent Noise

摘要

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 robustH∞filter can be designed by solving linear matrix inequalities (LMIs). Moreover, a mixedH2/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.