Abstract:

Recently, interest in swarm intelligence optimization techniques (Particle Swarm Optimization, Genetic Algorithm, Tabu Research Algorithm, etc.) has increased and this issue has become the focus of attention especially for scientists. Optimum controller parameters can be found with less experience in a short time by using optimization algorithms. PID is a type of controller which is widely used in the industry. The characteristic of the PID controller has effected the controller coefficients and optimum parameters must be tuned for good control. The speed control of a DC motor that is commonly used in practice is one of the important problems in engineering. DC motors are economical as well as important electrical machines of both industrial applications and our daily life due to their ease of control and optimum moment-speed characteristics. The best values of Kp, Ki and Kd with classical methods are a time consuming problem. The use of meta-heuristic methods gives both speed and accuracy in finding optimum values. In this study, optimum parameters are determined for a PID controller using Artificial Bee Colony Algorithm (ABC). The PID controller is designed as a speed controller for DC motor and simulated. In the literature, generally, the optimization was carried out with a single cost function or a combination of different functions with appropriate gains. This type of approach does not fit for the PID controller optimization since the effect of each parameter is different on the output of the system. Because of this reason, the optimum value of each parameter has been searched separately by using the three-channel cost function. The proposed algorithm in the present study gives more successful results than the traditional ABC algorithm having a single cost function.

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