Open AccessOptimization Control of DC Motor with Linear Quadratic Regulator and Genetic Algorithm Approach
Author(s) -
Majed D. Youns,
Abdulla I. Abdulla,
Salih M. Attya
Publication year - 2013
Publication title -
mağallaẗ tikrīt li-l-ʻulūm al-handasiyyaẗ/tikrit journal of engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 2312-7589
pISSN - 1813-162X
DOI - 10.25130/tjes.21.1.05
Subject(s) - control theory (sociology) , linear quadratic regulator , overshoot (microwave communication) , engineering , optimal control , control engineering , genetic algorithm , settling time , controller (irrigation) , control (management) , step response , computer science , mathematics , mathematical optimization , agronomy , artificial intelligence , biology , electrical engineering
This paper presents LQR and GA controllers which applied to control the speed of a DCmotor and to maintain the rotation of the motor shaft with particular step response. Inthe state space, the control strategy is the states feedback and the most used techniquesare the LQR. Liner quadratic regulator (LQR) provides an optimal control law for alinear system. It’s a control strategy based on minimizing a quadratic performanceindex. In despite of the good results obtained from these method, the control design isnot a straight forward task due to the trial and error method involved in the definition ofweight matrices. In such cases, may be hard tuning the controller parameters in order toobtain the optimal behavior of the system. In this work, it proposes a states feedbacktechnique in which there are no trial and error processes involved and the control designis carried out to fulfill specifications, for minimize overshoot and minimize settling andrising times. The proposed technique is based on the use a genetic algorithms. Theobtained results show that is possible to design controllers which fulfill designspecifications.