An improved type-2 fuzzy logic controller design based on genetic algorithm
Taoyan Zhao, Ping Li, Jiangtao Cao, Honghai Liu · 2017
In this paper, an improved interval type-2 fuzzy logic controller based on genetic algorithm is presented to deal with the problem of losing uncertain information in the type reduction process of interval type-2 fuzzy logic controller. The four uncertain boundary values of interval type-2 fuzzy output are obtained by using interval type-2 fuzzy reasoning and the Wu-Mendel uncertainty bound type reduction algorithm. Then the controller outputs are re-optimized. The quantization factor, scaling factor and membership functions of interval type-2 fuzzy logic controller are evolved by using genetic algorithm. By constructing the fitness function of genetic algorithm as performance index, which can be directly related with the system output in order to improve the performance of the whole control system. Finally, the proposed method is implemented on the outlet temperature control system of ethylene cracking furnace, the simulation results demonstrate the effectiveness of the proposed control scheme.