Using Ant Colony Optimization Algorithm for Enhancing an Optimal PI Controller
نویسندگان
چکیده
In this paper we describe the application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of PI controller and to find the best optimal intelligent controller. The ACO algorithm is a bio-inspired optimization method that has proven its success through various combinatorial optimization problems. The parameters of the PI Controller are evaluated by an ant colony optimization by using an objective function based on position tracing error was constructed. The results obtained by the simulations are compared with previous work results obtained by a PI controller.
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