Speed Control of DC Motor under Reverse Torque Disturbance with Ant Colony Optimized PID Controller

Aksaray University Journal of Science and Engineering e-ISSN: 2587-1277 http://dergipark.gov.tr/asujse http://asujse.aksaray.edu.tr Aksaray J. Sci. Eng. Volume 5, Issue 1, pp. 8-19. doi: 10.29002/asujse.892979 Available online at Research Article Speed Control of DC Motor under Reverse Torque Disturbance with Ant Colony Optimized PID Controller Ömer KASIM* Department of Electrical Electronics Engineering, Faculty of Simav Technology, Kutahya Dumlupinar University, 43500, Turkey ▪Received Date: Mar 08, 2021 ▪Revised Date: Mar 25, 2021 ▪Accepted Date: Apr 03, 2021 ▪Published Online: Apr 21, 2021 Abstract Direct Current (DC) motors are widely used in industrial systems due to their high torque. In ensuring the stability and productivity of a system, it is important that the DC motor within the automation system reaches the reference speed value quickly and its speed remains constant under load. In this study, it is aimed to keep the speed value of DC motor constant under load by optimizing the gain parameters of the Proportional, Integral and Derivative (PID) controller, which is widely used in industrial applications. In the optimization of these parameters, the Ziegler Nichols method (ZNM) and the Ant Colony Optimization method (ACO) were examined comparatively in the simulation environment. PID parameters were determined by open loop responses under the running system with the ZNM. On the other hand, the most optimum solution was obtained among many parameters with the ACO method. Speed control of DC motor was performed with PID controller parameters which are determined according to the best ACO response. Simulation results are presented in comparison with the parameters of settling time, peak time, rising time and response of the system under load. As a result, PID controller run with Kp, Ki, and Kd parameters obtained by ACO algorithm generally gave better results than ZNM. Keywords DC Motor Speed Control, PID Controller, Ziegler Nichols method, Ant Colony Optimization method * Corresponding Author: Ömer KASIM, 0000-0003-4021-5412 2017-2021©Published by Aksaray University 8 Omer Kasim (2021). Aksaray University Journal of Science and Engineering, 5(1), 8-19. 1. INTRODUCTION In a control system design, it is advantageous to simulate the system by modeling instead of damaging the physical system or reconstructing it with changing parameters [1]. It is possible to improve the most optimum operating range of the Direct Current (DC) motor in the simulation environment. DC motors, which are the subject of this study and widely used in the industrial field, are easily linearly controllable [2]. PID controller is used in system control in approximately 90% of industrial applications [3]. In linear control processes, transient and steady state characteristics are improved by generally applying PID control strategy to DC motors [4]. This improvement is realized by determining the values of 3 parameters named as proportional gain coefficient (Kp), integral gain coefficient (Ki) and derivative gain coefficient (Kd). In the speed control of the DC motor, it depends on the optimum selection of Kp, Ki and Kd of the controller. In practice, these three parameters are adjusted manually by matching with the automation system and set them for all operating situations [5]. However, it is possible to find more optimum solutions if the analysis of the load cases that the system will be exposed to is made with optimization algorithms in the simulation environment. As a result, the advantages of commonly used PID and intelligent algorithm can be integrated to reduce parameter setting cost, improve tuning efficiency and system stability [6]. Various studies have been presented in the literature for the optimum selection of the gain parameters of the PID controller. The Ziegler-Nichols method (ZNM), which is the most classical form of these, is based on the open loop operation of the system [7]. Hammoodi et al. provided the speed control of DC motor with a PID controller. The authors designed the simulation environment by considering the electrical and mechanical parts of the dc motor separately. With this design, it is stated that when the reverse torque situation that will occur under load is simulated, the PID controller can keep the speed of the motor constant against the load [8]. Alqahtani et al. carried out speed control of DC motor without load in simulation environment with PI and PID controller. The authors explained that they got similar results from PI and PID controller in the simulation environment. However, they did not mention the control process of the DC motor under load [9]. Khan et al. simulated a DC motor under different torque loads. The authors designed the PID controller using the ZNM. They experimentally demonstrated that the PID controller obtained satisfactory results, especially under load [10]. Parnianifard et al. simulated 5 different DC motors with a PID controller. It was stated by the authors that models tested with multiple cycles using PI, PID and fractionalorder PID under different load conditions gave more durable results [11]. Faisal measured the Aksaray J. Sci. Eng. 5:1 (2021) 8-19 9 Omer Kasim (2021). Aksaray University Journal of Science and Engineering, 5(1), 8-19. speed response of the asynchronous motor in his study. The author analyzed the PID controller gain parameters obtained with the conventional experiment and the gain parameters obtained with the Ant Colony Optimization (ACO) algorithm. As a result of the analysis performed with an uncontrolled induction motor, it was explained that the ACO algorithm provides faster convergence with a minimum fit function. However, no analysis under load was included in the study [12]. Farahani et al. examined the improvement of rise time and settlement time in their work. The authors achieved very successful results by optimizing the fractional-order PID controller in their experimental work. However, the results of the ACO algorithm were not discussed in the study [13]. Dutta et al. obtained better sitting time with the PID controller parameters they optimized with the gray wolf optimization algorithm [14]. However, the torque situation changing with the load was not examined in this study. Although many techniques are successful in automatically adjusting the PID parameters, the robustness of the speed control of the DC motor depends on the optimum selection of PID controller Kp, Ki, and Kd gain parameters. Various algorithms for the best selection are presented in the literature. The most popular of these is the Ziegler-Nichols method. However, it is possible to choose more optimized parameters according to this method. For this purpose, optimization methods are preferred in parameter estimation. The ACO is capable of populationbased optimization has robustness and ease of use. This article presents a comprehensive experiments of PID controller optimization with the ACO method and th (...truncated)