Non-fragile sampled-data guaranteed cost control for bio-economic fuzzy singular Markovian jump systems

This study investigates the non-fragile sampled-data guaranteed cost control problem for a bio-economic singular Markovian jump system that is represented by the Takagi-Sugeno fuzzy model. The main intention of this study is to design a non-fragile sampled-data controller for the considered model to handle the issue of tax fluctuations by means of showing that the closed-loop system is regular, impulse free and stochastically finite-time bounded. Sampled-data controller is the one where the continuous system is controlled by the digital control algorithms. By introducing a proper Lyapunov-Krasovskii functional and using linear matrix inequality (LMI) approach, a new set of criteria is obtained in terms of LMIs for achieving the required result. More precisely, by solving LMIs, an upper bound for the cost function can be obtained. Finally, a simulation result is given to illustrate the effectiveness of the proposed control design.