Multi-objective robust filtering for fuzzy singularly perturbed systems with Markov-switching

In this paper, we expect to design a multi-objective robust filter for fuzzy singularly perturbed systems (SPSs) with Markov switching. By utilizing the Takagi and Sugeno (T-S) fuzzy model and the Markov jump model, both the nonlinearity and the sudden changes in the parameters or structures are considered in the description of SPSs. Based on some acquired conditions, the final filtering error system can be assured stochastically stable with a prescribed dissipative performance index. Finally, the filter gains can be gained by solving these conditions.