Improve DC Motor System using Fuzzy Logic Control by Particle Swarm Optimization in Use Scale Factors

In our system design, we used Particle Swarm Optimization (PSO) Algorithm because we want to design a DC Motor system with Fuzzy logic control to provide high angular speed and low error. The DC Motor system is configured by MATLAB SIMULINK platform R2012a to be find which Method or algorithm will be used with the conventional controller the Proportional Derivative (PD) controller that will be improve this system like Particle Swarm Optimization (PSO) Algorithm has been utilized to improve from The performance of the Designed system. And the use of Particle Swarm Optimization (PSO).Algorithm will improve the Fuzzy logic control when connect with PD controller because PSO it will looking for the best 3 scales factors(gain) among 50 birds and we have set the no. of birds in PSO algorithm code and number of iteration is 10 it will make 50*10=500 process to find the best 3 gains to be used in the scale factors of fuzzy logic control instead of the static values that we have been putted statically it will be received dynamically from PSO algorithm and after that we have token these gains and insert it to fuzzy logic control scale factors. In this paper, three tests are taken to demonstrate between different proposals to studying the-DC Motor system based the Proportional Derivative (PD) controller with various formats by use Proportional Derivative (PD) controller with Fuzzy logic control and also by use this controller with fuzzy logic control by use the algorithm of Particle Swarm Optimization by test the angular speed and also the error to improve which one of them is the best, the designed system to improve it by increasing the angular speed and reduce the error this will improve the efficient of it.