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A Comparative Study of Artificial Bee Colony versus PSO and GA for Optimal Tuning of PID Controller
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Artificial Bee Colony (ABC) algorithm is one of the most recently used optimization algorithms. ABC algorithm has been extracted from the intelligent behavior of honeybees swarm. This work compares the performance of ABC algorithm with that of GA and PSO algorithms in tuning the proportional-integral-derivative (PID) controllers for the ball and hoop system which represents a system of complex industrial processes, known to be non-linear and time variant. Simulation results show that ABC algorithm is highly competitive, often outperforming PSO and GA algorithms.
Keywords
Evolutionary Algorithms, PID Control, Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithms (GA).
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