In this paper, the ACO (Ant Colony Optimization) algorithm is implemented as an adjustment mechanism for the PID controller. The objective of this hybrid controller is to improve the performance of a servo control of a loopback system or closed process. The search technique using the ACO algorithm is applied to find for the best gain parameters of the PID controller. The setting of a PID consists in obtaining an adequate response of the process. The objectives are robustness, speed and precision. One of the applications is the control of a manipulator arm using a DC servomotor as actuator. This study introduces the DC Servo PID controller design using SISTOOL PID Auto Tuning for high order models and implemented on an Arduino model Mega 2560 controller using the MATLAB / Simulink interface package. Better controller design can be achieved by utilizing PID optimization by the Ant Colony Method (ACO).The results of the simulation show the performance and efficiency of the use of the ACO algorithm for PID adjustment
PID corrector, ACO-PID control, Sisotool, DC Servo Motor, Arduino Mega 2560
Cite this paper
Sid Ahmed Dahmane, Abdelwahab Azzedine, Abdelkader Megueni. (2020) Ant Colony Optimization Algorithm Based on Optimal PID Parameters for a Robotic Arm. International Journal of Control Systems and Robotics, 5, 8-13
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