Relaxed filtering designs for continuous-time nonlinear systems via novel fuzzy H? filters
This paper investigates the problem of H? H ? filtering for continuous-time nonlinear systems in the TakagiSugeno (TS) fuzzy model form. Different from the existing fuzzy H? H ? filters, a novel filter is designed such that the filter matrices are homogeneous polynomially parameter dependent on membership functions with an arbitrary degree. By developing both the novel fuzzy H? H ? filter and a kind of slack matrix variable technique, relaxed filtering conditions for implementing the H? H ? filter are proposed in terms of linear matrix inequalities (LMIs), while the filtering error system preserves a smaller prescribed H? H ? performance index than the existing ones. Finally, a numerical example is given to illustrate to show the effectiveness of the proposed approach.
homogeneous polynomial relaxed filtering condition state estimation h? h ? filter h? h ? h? h ? h ? slack variable technique