Hybrid approaches for regional Takagi–Sugeno static output feedback fuzzy controller design

This paper proposes a Takagi–Sugeno (T–S) fuzzy region model to relax the original one. Such switching concept has got rid of the complicated analysis of parallel distributed compensation (PDC). By mixing genetic algorithm (GA) and linear matrix inequality (LMI), we present a new hybrid approach about the static output feedback controller design. It is unlike other researches that involve abstruse mathematic transformations and system constraints that are difficult to find. In this paper, we fix the static output feedback gains by GA to solve the non-convex problem. It is proved that the existence of a set of solvable non-linear matrix inequality (NLMI) suffices to guarantee the stabilization of T–S fuzzy region system in H ∞ sense. Numerical examples are given to illustrate the effectiveness of the algorithm and validate the new method.