Applications of Modern Optimization Methods for Controlling Parallel Connected DC-DC Buck Converters
This paper presents the application of on-line Particle Swarm (PSO) and Ant Colony Optimization (ACO) techniques based-state feedback controllers for adjusting and tuning the output voltage and current of parallel DC-DC buck convectors. The objective of control system is to balance the current of each converter and to highly improve the output voltage performance of the parallel buck converter. Given a system with large variations of input voltage and load, it is necessary to guarantee good performance of the controller for large variations of operating point. The simulation results of PSO and ACO-based controllers systems are compared. The results were obtained show how PSO and ACO can effectively and efficiently optimize the dynamic performance of the adopted converter under variations in load and input voltage as well as in reference voltage.
Keywords: Particle Swarm Optimization (PSO), state feedback controller, Optimization, Ant Colony Optimization (ACO) , DC-DC converters, parallel buck system
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ABOUT THE AUTHOR
Ali S. Al-Dmour
Mutah University
Ali S. Al-Dmour
Mutah University
