Optimal Tuning of Servo Motor Based Linear Motion System Using Optimization Algorithm

• Published in: Journal of electrical engineering & technology 2022-11, Vol.17 (6), p.3565-3580
• Main Authors: Ramesh, H., Xavier, S. Arockia Edwin
• Format: Article
• Language: English
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics
• ISSN: 1975-0102; 2093-7423
• DOI: 10.1007/s42835-022-01149-5

Linear motion systems with servo drives are employed in high-precision machine tool applications. The PID controller is commonly employed in servo-based linear motion systems to correct positioning inaccuracies caused by thermal expansion of the ball screw assembly and encoder measurement. Different classical and heuristic approaches are used for optimal PID tuning of servo controllers used in linear motion systems. Integral-based or performance-index- based error minimizing functions found in the literature do not meet all of a dynamic system's performance requirements. In this paper, the multi-objective cost function using both the integral time absolute error function and performance index parameters such as rise time, settling time, and peak overshoot is formulated based on the non-dominated solutions of the pareto front obtained using a multi-objective genetic algorithm (MOGA). The proposed objective function is used to tune the PID controller model of a linear motion system using the particle swarm optimization algorithm, the BAT algorithm, the whale optimization algorithm, and the aquila optimizer. The simulation and validation results show that the MOGA-based multi-objective function outperforms standard error minimizing objective functions and classical fractional order PID control algorithms in tuning PID Servo controllers of linear motion systems.