Paper Title
Design A Hybrid Intelligent Controller (Fuzzy-Based Ant Colony Algorithm) For Improving A Tracking Performance of Actual Output Response of SEDC Motor Under The Effect of External Disturbances

For electrical drives good dynamic performance is mandatory so as to respond to the changes in command speed and torques, so various speed control techniques are being used for real time applications. The speed of a DC motor can be controlled using various controllers like PID Controller, Fuzzy Logic Controller, Ant Colony Algorithm (ACA) and Hybrid Fuzzy-ACA Controller. Fuzzy-ACA Controller is recently getting increasing emphasis in process control applications. The paper describes application of Hybrid Fuzzy-ACA Controller in an enhancement of stability and accuracy of the SEDC Motor under the effect of the external disturbances and noise that is implemented in MATLAB/SIMULINK. The simulation study indicates the superiority Hybrid Fuzzy-ACA Controller over the Ant Colony Algorithm (ACA) and fuzzy logic controller separately. This control seems to have a lot of promise in the applications of power electronics. The speed of the SEDC motor can be adjusted to a great extent so as to provide easy control and high performance. There are several conventional and numeric types of controllers intended for controlling the SEDC motor speed and executing various tasks: PID Controller, Fuzzy Logic Controller; or the combination between them: Fuzzy-Swarm, Fuzzy-Neural Networks, FuzzyGenetic Algorithm, Fuzzy-Ants Colony, Fuzzy-Particle Swarm Optimization. We describe in this paper the use of Ant Colony Algorithm (ACA) for designing an optimal fuzzy logic controller of a SEDC Motor. In this case, our approach will optimize the membership functions of a fuzzy logic controller (FLC) using ACA and the obtained results were simulated on Matlab environment. Excellent flexibility and adaptability as well as high precision and good robustness are obtained by the proposed strategy.