Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

Abstract

In this paper, intelligent control of a reluctance synchronous motor by an emotional controller, considering the effect of magnetic saturation on implementation, is analyzed; the maximum torque per ampere (MTPA) strategy is provided. According to the application of the proposed control scheme, the structure adequately performs the control of speed and magnetic flux of the reluctance synchronous motor drive. Additionally, the application of intelligent control based on an emotional learning system has provided adequate results to create a proper control process. The control function of a SynRM drive based on vector control in a rotor machine was compared with another based on emotional controllers and a PI controller regulated by genetic algorithms. The result of this comparison was the improvement of control functions by the controller based on the emotional controller. In addition, the MTPA based on search algorithms was well implemented in different situations. Due to its simplicity and independence from system parameters, the emotional controller can be considered as a potential operational method in the industry.