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The purpose of this paper is to investigate and implement a novel approach to learning control for permanent magnet synchronous motor (PMSM) drive system using a hybrid recurrent fuzzy neural network (HRFNN) control. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMSM servo drive. Then, a HRFNN speed control system that combined supervisor control, RFNN and...
The purpose of this paper is to investigate and implement a novel approach to learning control for permanent magnet synchronous motor (PMSM) drive system using a hybrid recurrent fuzzy neural network (HRFNN) control. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMSM servo drive. Then, a HRFNN speed control system that combined supervisor control, RFNN and...
An adaptive backstepping control using fuzzy neural network (FNN) uncertainty observer is proposed to control the rotor position of a synchronous reluctance (SynRel) motor drive in this paper. First, the field-oriented mechanism is applied to formulate the dynamic equation of the SynRel motor servo drive. Then, an adaptive backstepping approach is proposed to compensate the uncertainties in the motion...
The switched reluctance motor (SRM) drive system using hybrid fuzzy neural network (HFNN) controller is developed to control electric motorcycle in this paper. First, the dynamic models of a SRM drive system and electric motorcycle are builted though experimental tests and parameters measurements. Then, a HFNN speed control system that combined supervisor control, FNN control and compensated control...
The purpose of this paper is to implement a novel approach to learning control for torque-ripple reduction of switched reluctance motor (SRM) using an adaptive fuzzy neural network (AFNN) control. First, the dynamic models of a SRM drive system are builted though SRM experimental tests and parameters measurements. Then, in order to reduce torque ripple, an AFNN speed control system that combined FNN...
An adaptive backstepping recurrent fuzzy neural network (ABRFNN) control system is proposed to control the rotor position of a synchronous reluctance motor (SynRM) servo drive in this paper. First, the field-oriented mechanism is applied to formulate the dynamic equation of the SynRM servo drive. Then, an adaptive backstepping approach is proposed to compensate the uncertainties in the motion control...
The purpose of this paper is to investigate and implement a novel approach to learning control for torque-ripple reduction of switched reluctance machines (SRM) using a supervisor hybrid recurrent fuzzy neural network (SHRFNN) control. First, the dynamic models of a SRM drive system are built though SRM experimental tests and parameters measurements. Then, in order to reduce torque ripple and control...
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