Multi objective ant algorithm to parameter optimized of PID controller and compare to genetic algorithm

In this paper, design method for closed-loop auto-tuning of a PID controller based on the Multi-Objective Ant Algorithm (MOAA) is proposed. The pheromone update rule has combined low and high cost path value such that low cost path value pheromone considerably and high cost path value decreased rapidly. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controller by minimizing the multi-objective function which is based on integral square error, rise time, maximum overshoot and settling time. Comparing the MOAA with Ziegler-Nichols, genetic algorithm and ant colony optimization, simulation results demonstrate that the new tuning method has a better control system performance.