Tuning of a speed control system for DC servo motor using genetic algorithm

Abstract EN

A Dc servo motor system is one of the widely used variable speed drives in industrial production, process automation and building technology worldwide, they are intended and designed to use in motion control applications which require high accuracy positioning, quick reversing and exceptional performance.

It is a widely used device for many applications, starting from simple industrial tasks to precise manufacturing applications such as in robotics.

It uses a PID controller in order to obtain an error feedback signal, and thus produces a stable angular speed.

However, PID controllers produce various problems such as poor and unstable responses during the frequent presence of disturbance and noise.

This paper aims to implement a parametric second-order model of a servo motor via raw data extracted from real experiments, an optimization technique named Genetic algorithms (GA) was used for identifying of the model parameters, also to design an efficient PI controller that provides a fast response, less rise time and sufficient settling time.

The parameters of the designed PI controller were also selected based on using a GA optimization technique with three popular common performance criteria, namely, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE).

Moreover, the performance of the optimized PI controller was testified and evaluated when the servo motor is operating under varying inertia loads The experimental results show that the GA PI controller with the ITAE criteria is more proficient in enhancing the angular speed stability and also in meeting the operational demands compared with other traditional objective functions.