A Novel Parent Selection Operator in GA for Tuning of Scaling Factors of FKBC
Mohammad Azeem · 2006
An exhaustive list that encompasses a wide range 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 author has proposed a modification to the Sung's [Sung Hoon Jung, "Queen bee evolution for genetic algorithms", Electronics letters, 20th March 2003, Vol.36 No. 6 pp. 575-576] GA. The proposed GA utilizes the weighted crossover operator. A fitness function, which guides the evolution process, is defined as inverse of integral time absolute error (ITAE). The proposed method is applied, for the tuning of input and output scaling factors of FKBC, on four different types of complex non-linear systems. The simulation results are encouraging.