Abstract

In this paper hybridization between two optimization methods that are Genetic Algorithm (GA) and Artificial Immune System (AIS) is presented for determining the optimal proportional-integral derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The brushless DC motor is modeled in Simulink and the Hybrid GA-AIS algorithm is implemented in MATLAB. The capability of overcoming the shortcomings of individual algorithms without losing their advantages makes the hybrid techniques superior to the stand-alone ones based on the dominant purpose of hybridization. The Hybrid GA-AIS method has superior features, stable convergence characteristic and good computational efficiency. The results that get it from hybridization are improved compares with that results can get from GA and AIS alone.  The hybrid GA-AIS consists of two processes, the first one is a genetic algorithm (GA) is typically initialized population randomly. Hybridization is faster and more accurate compare with GA AIS alone.

This work is licensed under a Creative Commons Attribution 4.0 License.