PID Controller tuning optimization for Computer Numerical Control using particle Swarm Optimization algorithm

Abstract

In this thesis, an artificial intelligence method Particle Swarm Optimization (PSO) algorithm is presented for determining the optimal proportional-integral-derivative (PID) controller parameters of a servo motion system used in Computer Numerical Control (CNC). This thesis demonstrates in detail on how to employ the PSO method to search efficiently the optimal PID controller parameters of the servo motor. In order to assist estimating the performance of the proposed PSO-PID controller is modeled using MATLAB environment. The proposed approach yields better solution in term of rise time, settling time, maximum overshoot and steady state error condition of the system. Compared to conventional Ziegler – Nichols method, the proposed method was indeed more efficient and robust in improving the step response of the servo motor.