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Paper Title

DC Motor Speed Control using Fuzzy Gain Controller with Evolutionary Algorithm

Article Type

Research Article

Issue

Volume : 6 | Issue : 6 | Page No : 13-16

Published On

December, 2019

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Abstract

The PID controllers are used to achieve the required speed and position control of the DC motors. The soft computing techniques such as particle swarm optimization (PSO) method, Genetic Algorithm (GA) method are used for determining the optimal proportional-integral derivative (PID) controller parameters to simplify the tuning procedures. Recently FUZZY-PID controllers can improve the performance with higher accuracy. But tuning the FPID controller gains (Kp,Ki,Kd,Ku) for desired performance is complex. This Paper presents a particle swarm optimization (PSO) method for optimal tuning of FUZZY-PID controller. The DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. Comparing with PSO PID method, the proposed method has more efficient in improving the step response characteristics such as, reducing the steady-state error; rise time, settling time and maximum overshoot.

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