Emotional Learning as a Cognitive Approach for High Performance Control of Permanent Magnet Stepper Motor

Stepper motors are introduced as certain electromechanical devices which vastly utilized in robotic industries, computer numerical control machines, and different actuators. Although open loop control offers an approximately acceptable performance, in higher stepping rate, the speed response is dealing with the large overshoot, a remarkable steady-state error and sometimes oscillations. Therefore, a closed loop configuration is indispensible to enjoy precise performance. This paper presents an application of Brain Emotional Learning Based Intelligent Controller (BELBIC) to satisfy the objective of speed control in Permanent Magnet Stepper Motor (PMSM).BELBIC is an intelligent controller that mimics the physiological model of emotional learning in mammalian’s brain. Fast response, high accuracy, significant decreasing in steady state error and less dependence to the dynamic modeling of the system introduce BELBIC as an eminent controller. Furthermore, robustness in presence of the disturbance and functional changes of the system is another positive point which must put into perspective. To verify these attributes, a fair comparison between the speed response corresponding to BELBIC and static PID has been done in this paper. The results clearly indicate the outstanding ability of BELBIC in more accurate speed tracking for the arbitrary reference signals with the least error and robustness of controller in presence of uncertainties.