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Hybrid Glowworm Swarm Optimization for Optimal Tuning PID Controller

Weiguo Zhao, Kui Li, Shaopu Yang, Liying Wang


Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many disciplines of science and engineering. A novel method to determine the optimal tuning of the PID controller using Hybrid Glowworm Swarm Optimization (HGSO) is proposed in this paper. The method combines the conventional Glowworm Swarm Optimization (GSO) framework with the heuristic crossover operation of GA and the Hooke-Jeeves method, which not only enables the HGSO enlarge the solution space in a global domain, but only improves its convergence speed. The method is applied to the optimal tuning of PID controller and is compared with standard GSO, the simulation experiments show the PID controller optimized by the proposed method has a fewer overshoot and a faster step response than its counterpart, the total performance of the system has been significantly improved.


PID controller, Glowworm Swarm Optimization, heuristic crossover operation, Hooke-Jeeves method.

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