A comparative study of various intelligent based controllers for speed control of IPMSM drives in the field-weakening region

Precise speed control of an Interior Permanent Magnet Synchronous Motor (IPMSM) drive becomes a complex issue due to the nonlinear nature of its developed torque. The system nonlinearity becomes severe when the IPMSM drive operates in the field weakening region. In order to achieve perfect control characteristics, the main purpose of this paper is to present a detailed comparison of various intelligent based controllers for flux weakening speed control of an IPMSM drive. In this paper, the Brain Emotional Learning Based Intelligent Controller (BELBIC), Genetic-Fuzzy Logic Based Controller (GFLBC), as well as genetic-PI based controller, are considered. BELBIC is a computational model of emotional processing mechanism in the brain. The effectiveness of the proposed BELBIC controller-based IPMSM drive is verified by simulation results at different operating conditions. Moreover, control regimes such as Maximum Torque Per Ampere (MTPA) control and flux weakening (FW) control as well as voltage and current constraints have been successfully applied. The results prove BELBIC’s perfect control characteristics, such as fast and smooth speed response, low maximum starting current, adaptability to speed and load changes and robustness to parameter variations, disturbance and sudden one-phase interruption.