Artificial bee colony with predator effect algorithm for proportional integral derivative controller tuning

Abstract

This paper proposes a novel artificial bee colony with predation effect (ABCPE) algorithm for tuning a proportional integral derivative (PID) controller. The mathematical model of ABCPE algorithm to introduce predator effect in the foraging behavior of artificial bees colony algorithm has been formulated. The proposed algorithm has been tested on tuning problems of different process models. The simulation results reveal that the closed-loop responses are relatively fast and non-oscillatory as compared to the frequency response analysis method for reference tracking. Further, the results obtained using ABCPE are also compared with other evolutionary algorithms. The exhaustive analysis shows that the ABCPE-based solution approach leads to a set of tuning parameters having smaller overshoot, less setting time, and rise time compared to other solution approaches. The stability analysis using Nichols plot reveals that the phase margin of proposed algorithm is higher as compared to other tuning methods. Finally, the convergence behavior and robustness analysis reveals the effectiveness of the proposed approach to solve engineering design problems.