Comparative Studies on Evolutionary Computational Techniques for Speed Control of A DC Motor

Abstract

Proportional-Integral-Derivative (PID) Controllers plays a significant role in many industrial and commercial applications. Designing of PID controller is always a challenging problem especially for high order systems. It is known that PID Controller is employed in every aspect of industrial automation. The PID Controller applications are spanned from small industry to higher technology industries. Hence, the problem is always how to optimize the PID Controller. Generally, initial designs obtained by all means need to be adjusted repeatedly through computer simulations until the closed-loop system performs or compromises as desired. This simulation involves the development of "intelligent" tools that can assist engineers to achieve the best overall PID control for the entire operating range. Self-tuning method for PID Controller using Evolutionary Computational (EC) Techniques capable of providing robust design. In this paper two types of tuning methods are presented, namely Genetic Algorithm and Modified Interactive Evolutionary Computation Method. The results obtained by them based on velocity control of DC motor and harmonic analysis are analysed and a comparative study of the two are presented. KEYWORDS: DC motor, PID, Genetic Algorithm, MIEC I.INTRODUCTIONPID Controller is a generic control loop feedback mechanism and is widely used in control system. PID Controllers use three basic behavior types or modes: P -proportional, I -integral and D -derivative. While proportional and integral are together used as single control mode, a derivative mode is rarely used on its own in control systems. Combinations such as PI and PD control are very often used in practical systems. A proportional-integral-derivative controller or commonly known as PID Controller is a generic control loop feedback mechanism (controller) widely used in industrial control systems. Therefore, a PID is the most commonly used feedback controller [1]. Such type of controller estimates fault rate as the difference between a considered method variable and a required set-point. The designed controller tries to reduce the error by correcting the process control inputs. The PID Controller algorithm consists of three distinct stable parameters, and is consequently termed as three-term control, they are proportional, integral and derivative values, denoted as P, I, and D. The weighed sum of these three events is deployed to regulate the process using a control constituent. A PID Controller is the most excellent controller. The controller has a potential to facilitate the organized act programmed for specific process needed by modifying the three parameters in a PID Controller algorithm. The block diagram of a PID Controller is shown in Fig. 1