DEVELOPMENT OF A CULTURAL ALGORITHM BASED-ARTIFICIAL BEE COLONY FOR IMPROVED PROPORTIONAL-INTEGRAL-DERIVATIVE CONTROLLER PARAMETER TUNING

📄 Project Abstract

This research is aimed at the development of a cultural-algorithm based artificial bee colony algorithm (CABCA) for improved Proportional Integral Derivative (PID) controller parameters tuning. The normative and situational knowledge inherent in cultural algorithm were utilized to guide the step size as well as the direction of evolution of Artificial Bee Colony (ABC) at different configurations, in order to combat the disparity between exploration and exploitation associated with the standard ABC, which results to poor convergence and optimization efficiency. Four variants of CABCA (CABCA(Ns), CABCA(Sd), CABCA(Ns+Sd) and CABCA(Ns+Nd)) were accomplished in MATLAB R2015a using different configurations of cultural knowledge. A total of 20 standard applied mathematical optimization test functions (Ackley, Michalewicz, Quartic, Sphere etc) were employed to evaluate the performance of each CABCA variant. The results indicated that CABCA(Ns) performed best in 4 test functions (20%), CABCA(Ns...