Identification of Position DC Motor and Control Using Fuzzy Type 2 Based PSO

Abstract

This paper presents identification of a position DC motor using least squares analysis to estimate the parameters of an ARX model .Type-2 fuzzy logic controllers is proposed as an alternative solution in the literature when a system has a large amount of uncertainties. This paper proposed an algorithm of interval fuzzy type 2 logic controller(PSOIT2FLC)with the optimized parameters using particle swarm optimization in the design of fuzzy controller for the position control of DC Motor. The performance of the proposed PSOIT2FLC is compared with that of its corresponding conventional PSO 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 conventiona genetic algorithm type -1 fuzzy controller to the response given with the proposed PSOIT2FLC scheme. Simulation works in MATLAB environment demonstrate that the PSO optimized fuzzy position controller became very strong, gives better results and possesses good robustness.