Performance Analysis of an Interior Permanent Magnet Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

This paper presents a novel Brain Emotional Learning Based Intelligent Controller (BELBIC) for controlling some of the parameters, such as speed, torque, quadrature and direct axis current and voltage of an Interior Permanent Magnet Synchronous Motor (IPMSM). PI controllers are widely used as speed controllers in industries. IPMSMs are characterized as complex, highly non-linear and time-varying dynamics. Conventional PID controllers are unable to sustain satisfactory performance for IPMSM running at high speeds, where the non-linearity is severe. The paper introduces a simple arithmetical model of emotional controller for ease of its implementation in a closed loop drive system..Moreover, control commands such as Maximum Torque per Ampere (MTPA) control and flux weakening (FW) control as well as voltage and current constraints have been successfully applied. Proto type IPMSM drive incorporating the proposed BELBIC has been successfully implemented in real time a user friendly interface based on LabView is used for controlling the system. Performance of the emotional controller is compared with Antiwindup PIcontroller. The simulation and experimental results demonstrate the effectiveness of the controller during the conditions of starting, step change in speed and load perturbations.