Abstract—Velocity control of DC motors is an important issue also shorter settling time is desired. In this paper at first a PID compensator which adjusted by genetic algorithm is designed then another compensator will be designed by combining two methods, Integral controller and optimal State Feedback controller (I&S.F.). In the second compensator, design specifications, depend on choosing weighting matrices Q and R, we use the Genetic Algorithm (GA) to find the proper weighting matrices. Of course Kalman filter is used as a system observer in order to increasing the system robustness. Then the performance of the control techniques is compared in terms of rise time, settling time, tracking error, and robustness with respect to modeling errors and disturbances. The controller design process and implementation requirements are also discussed. Then the comparison between the PID control and the optimal control shows that the optimal controller significantly reduced the overshoot, settling time and has the best performance encountering with system uncertainties. Also we apply noise and 20% parameters variation for DC motor and compare the results. According to the simulation results, the second controller has better performance than the PID controller.
Index Terms—DC Motor, Genetic Algorithm, Kalman Filter, Optimal Control, PID Controller
M. B. B. Sharifian is with the Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. (Phone: +98 411 3294120).
R. Rahnavard is with Azerbyjan Regional Electric Company, Tabriz, Iran.
Cite: M. B. B. Sharifian, R. Rahnavard and H. Delavari, "Velocity Control of DC Motor Based Intelligent methods and Optimal Integral State Feedback Controller," International Journal of Computer Theory and Engineering vol. 1, no. 1, pp. 81-84, 2009.
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