Robust H2/H∞ Filter Design for a Class of Nonlinear Stochastic Systems with State-Dependent Noise

نویسندگان

  • Weihai Zhang
  • Bor-Sen Chen
  • Li Sheng
  • Ming Gao
  • Jun Hu
چکیده

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.

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تاریخ انتشار 2014