Modified queen bee evolution based genetic algorithm for tuning of scaling factors of fuzzy knowledge base controller

There are wide ranges of combination for genetic algorithm (GA) operators exist in the literature. Most of them have been applied on different type of tuning application for fuzzy knowledge base controller (FKBC). In this paper authors proposed a modification to the Sung's GA. The proposed GA utilizes the weighted crossover operator. A fitness function, which guides the evolution process, which is defined as inverse of integral absolute time error (IATE). The proposed method is applied, for the tuning of input and output scaling factors of FKBC, for two complex non-linear systems. The simulation results are encouraging.