Optimal Tuning of PID controller using ant colony optimization algorithm in a networked control system

Abstract

- In this paper, we used the Ant Colony Optimization algorithm (ACO) for tuning PID controller in order to use this controller in control processes over networks, which usually suffers from time delay problem which affects noticeably the control signal quality, and so the response quality. We employed the controller in a position DC motor control system with taking in consideration the presence of different time delays when transferring the control signal. The results showed the effectiveness of ACO in tuning PID controller to reduce the effect of time delays on response quality. We modeled a DC motor control system using the Matlab / Simulink environment. The results showed the effectiveness of ACO as a method of tuning PID to reduce the effect of time delays on response quality when comparing with traditional experimental methods. We used the performance criterions that used in evaluating control systems performance as cost functions for ACO. The ACO gave the best response of the proposed control system when using Integral Absolute Error as a cost function. With 200 ms of delay, ACO gave the least rise time 8.43 seconds with the least settling time 0.92 seconds, with a relatively small overshoot 3.27%. It also gave close values of each performance criterion, at different time delays 100, 200, 300 ms.