A HYBRID INTEGRATION OF FUZZY LOGIC – BASED CONTROLLERS AND METAHEURISTIC – INSPIRED OPTIMIZATION METHODS

This study proposes an effective integration of fuzzy logic controllers and bioinspired optimization mechanisms to deal with a large number of complex control problems. In this co-operation, PI-type fuzzy logic - based controller, which is considered to be an intelligent control candidate to replace with a conventional regulator i.e. PID, has several scaling factors to be necessary determined. The metaheuristic optimization methods, such as genetic algorithm (GA) and artificial bee colony (ABC), are applied to successfully optimize these factors. As a result of this hybrid integration, the proposed controllers are completely able to obtain much better control performances, outperforming the conventional regulators. This paper firstly presents a procedure to design this effective integration in details. Furthermore, a case study with various simulation scenarios implemented in MATLAB/Simulink package will be provided with significant results obtained to demonstrate the feasibility and effectiveness of the proposed control methodologies.