Type-2 Fuzzy Logic Controllers Based Genetic Algorithm for the Position Control of DC Motor

Mohammed Zeki Al-Faiz, Mohammed S. Saleh, Ahmed A. Oglah

Department of Computer Engineering, Al-Nahrain University, Baghdad, Iraq.
Department of Control & Systems Engineering, University of Technology, Baghdad, Iraq.
Department of Electronics Engineering, Diyala University, Diyala, Iraq.

DOI: 10.4236/ica.2013.41015                

Abstract

Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.

Keywords

Type-2 Fuzzy Logic Controller; Genetic Algorithm; DC Motor

Conflicts of Interest

The authors declare no conflicts of interest.

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