Comparison of Performance Measures of Speed Control for a DC Motor Using Hybrid Intelligent Controller and Optimal LQR

Author:

Narmadha T. Velayudham1,Baskaran Chackaravarthy1,Sivakumar K.1

Affiliation:

1. St.Joseph’s College of Engineering

Abstract

-In this paper , performance of fuzzy PD , fuzzy PI , fuzzy PD+I , fuzzy PID controllers are evaluated and compared. This paper also describes the speed control based on Linear Quadratic Regulator (LQR) technique. The comparison is based on their ability of controlling the speed of DC motor, which merely focuses on performance index of the controllers, and also time domain specifications such as rise time, settling time and peak overshoot. The controller is modelled using MATLAB software, the simulation results shows that the fuzzy PID controllers are the best performing candidates in all aspects but it as higher overshoot and IAE in comparison with optimal LQR. The Fuzzy PI controller exhibited null offset but suffers from poor stability and peak overshoot, whereas the fuzzy PD controller has fast rise time, with no overshoots but the IAE is much greater. Thus, the comparative analysis recommends fuzzy PID controller but it is usually associated with complicated rule base and tedious tuning. To circumvent these problems, the proposed LQR controller gives better performance than the other controllers.

Publisher

Trans Tech Publications, Ltd.

Reference16 articles.

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2. Neenu Thomas and Dr. P. Poongodi, Position Control of DC Motor Using Genetic Algorithm Based PID Controller, Proceedings of the World Congress on Engineering 2009 Vol. II, WCE2009, July 1-3, 2009, London, U. K.

3. Boumediene Allaoua, Barhim Gasbaoui and Barhim Mebarki, Setting Up PID DC Motor Speed Control alteration Parameters Using Particle Swarm Optimization Strategy, Leonardo Electronic Journal of Practices and Technologies, ISSN 1583-1078, Issue 14, January-June 2009, pp.19-32.

4. Mehmet Karadeniz, Ires Iskender , Selma Yüncü , 'Adaptive Neural Network Control of a DC motor, ELECO 2003, Bursa, Turkey.

5. Firas Mohammed To'aima, Optimal Control of Governor and Exciter for Turbogenerator using LQG, Baghdad University, College of Engineering, PhD Thesis, November2006.

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