Brain emotional learning based intelligent controller for stepper motor trajectory tracking

摘要: Excellent attributes of permanent magnet stepper motor (PMSM) make it prominent in robotic, aerospace, and numerical machine applications. However, the problem nonlinearity presence mechanical configuration changes, particularly precision reference trajectory tracking, must be put into perspective. In this paper, a novel cognitive strategy based on emotional learning limbic system mammalian’s brain is employed to establish an intelligent controller order provide necessary control actions as achieve tracking rotor speed different circumstances. Brain (BELBIC) model free controller, independent dynamic variations that occurs system, can taken account outstanding option for nonlinear Fast response, high accuracy, ability disturbance rejection introduce BELBIC eminent controller. To verify these attributes, test beds have been simulated Matlab Simulink environment performance investigated. For further illumination, classic called static proportional-integral-derivative (PID) also applied then comprehensive comparison, both certain uncertain condition, between results proposed controllers done. Uncertain situation provided by applying load torque variation parameters PMSM. The simulations clearly indicate with accuracy arbitrary signals conspicuous robustness uncertainties.   Key words: Permanent motor, learning, uncertainty, robustness.