Speed Control of Dc Motor
IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) ISSN: 2278-1676 Volume 3, Issue 6 (Nov. - Dec. 2012), PP 41-48 www.iosrjournals.org
Speed Control of Dc Motor Using Fuzzy Logic Technique
1
1, 2, 3
J. N. Rai, 2Mayank Singhal, 3MayankNandwani
Department of Electrical Engineering, Delhi Technological University
Abstract:This project uses FUZZY LOGIC TECHNIQUE in estimating speed and controlling it for DC motor.
The rotor speed of the dc motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed of DC Motor, especially when the motor and load parameters are unknown. Such a control scheme gives very accurate and precise result in very short time. The fuzzy logic controller employs if-else form programming of the various conditions to control the motor speed.
I.
Introduction
Direct current (DC) motors have been widely used in many industrial applications such as electric vehicles, steel rolling mills, electric cranes, and robotic manipulators due to precise, wide, simple and continuous control characteristics. The development of high performance motor drives is very important in industrial as well as other purpose applications. Generally, a high performance motor drive system must have good dynamic speed command tracking and load regulating response. DC drives, because of their simplicity, ease of application, reliability and favourablecost have long been a backbone of industrial applications. DC drives are less complex with a single power conversion from AC to DC. DC drives are normally less expensive for most horsepower ratings. DC motors have a long tradition of use as adjustable speed machines and a wide range of options have evolved for this purpose. In these applications, the motor should be precisely controlled to give the desired performance. Traditionally rheostatic armature control method was widely used for the speed control of low power dc motors.
Speed Control of Dc Motor Using Fuzzy Logic Technique
1
1, 2, 3
J. N. Rai, 2Mayank Singhal, 3MayankNandwani
Department of Electrical Engineering, Delhi Technological University
Abstract:This project uses FUZZY LOGIC TECHNIQUE in estimating speed and controlling it for DC motor.
The rotor speed of the dc motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed of DC Motor, especially when the motor and load parameters are unknown. Such a control scheme gives very accurate and precise result in very short time. The fuzzy logic controller employs if-else form programming of the various conditions to control the motor speed.
I.
Introduction
Direct current (DC) motors have been widely used in many industrial applications such as electric vehicles, steel rolling mills, electric cranes, and robotic manipulators due to precise, wide, simple and continuous control characteristics. The development of high performance motor drives is very important in industrial as well as other purpose applications. Generally, a high performance motor drive system must have good dynamic speed command tracking and load regulating response. DC drives, because of their simplicity, ease of application, reliability and favourablecost have long been a backbone of industrial applications. DC drives are less complex with a single power conversion from AC to DC. DC drives are normally less expensive for most horsepower ratings. DC motors have a long tradition of use as adjustable speed machines and a wide range of options have evolved for this purpose. In these applications, the motor should be precisely controlled to give the desired performance. Traditionally rheostatic armature control method was widely used for the speed control of low power dc motors.
References: [1] [2] [3] [4] [5] [6] FUZZY AND SOFT COMPUTING- Jyh-shing, Roger Jang, Chuen-Tsai Sun K. B. Mohanty,“Fuzzy remote controller for converter DC motor drives” , Parintantra, Vol. 9, No. 1, June 2004 Zimmermann, H. (2001). Fuzzy Set Theory And Its Applications. Boston: Kluwer Academic Publishers. ISBN 0-7923-7435-5 Yager, Ronald R, Filev, Dimitar P. (1994). Essentials of Fuzzy Modelling and Control. New York: Wiley. ISBN 0 -471-01761-2 Santos, Eugene S. (1970). “Fuzzy Algorithms”. Information and Control 17 (4) B.C Kuo–Digital Control Systems-2 nd Edition www.iosrjournals.org 48 | Page