Optimization of PID Controller with Metaheuristic Algorithms for DC Motor Drives: Review

Abstract

Direct Current (DC) motors are broadly used in various industrial applications such as robotics, automobiles, toys and for many other motoring purposes. This is attributable to their extraordinary flexibility, durability and low implementation cost. It is essential to control the speed, position, torque and other variables of the DC motor to achieve the needed performance depending on the area of application. Many classical techniques have been used in the past to control the DC motor, however, such methods typically take a long time, particularly when used for complex nonlinear systems. The application of metaheuristic algorithms as a means of implementing Artificial Intelligence (AI) in this area has proven to be highly effective in overcoming these shortcomings. In recent decades, metaheuristic algorithms have become increasingly prevalent due to their tremendous success in addressing a number real-world optimization challenges in various fields of human activities extending from economic, pharmaceutical and industrial applications to intellectual applications. This review, therefore, presents the optimization of the PID controller with metaheuristic algorithms for controlling the DC motor drives. A short description for each algorithm is presented along with papers published in various renowned journals. For a robust review, the application of various forms of PID controller, as well as different types of DC motors are examined. Finally, the paper presents some open issues and future directions for research.