Abstract: Because of the widespread use of motors, controlling their speed and position control are important. Different types of controllers for electric motors can confirm this statement. Many methods such as PID controllers and intelligent controllers have been proposed for motor control. This study aims to provide a new method for intelligent motor control using fuzzy controller type-2. After measuring motor parameters, a fuzzy controller with two inputs controls error and changes to minimize the errors in the shortest time possible. However, the extraction of rules and membership functions which is often based on trial and error, time-consuming and needs a specialist is a common problem. Evolutionary algorithms are a kind of search algorithm based on natural selection mechanism and a valid method for efficient and effective solution search process. In this method, Particle Swarm Algorithm (PSO) is used to determine type-2 fuzzy membership functions. The proposed method is simulated using data from a motor with MATLAB and in SIMULINK environment.
Mohahammad Javad Tajadini and Majid Mohammadi, 2016. Optimized Control of Servo Motor Speed Applying Type-2 Fuzzy. Journal of Engineering and Applied Sciences, 11: 240-251.