No abstract

An implementation for sinusoidal current control of a slotless Permanent Magnet Synchronous Motor (PMSM) with discrete Hall sensor position feedback is presented. To estimate the rotor position of the slotless PMSM, a flux estimation technique is used that takes advantage of the slotless machine's characteristically low inductance to limit flux estimation error. The rotor position is estimated using a reference model and the measured phase currents and voltages. At startup and very low speeds, discrete Hall sensors are used to limit the position estimation error to approximately 30 electrical degrees and to prevent the flux estimators from drifting due to measurement noise and offset. The proposed sinusoidal control method reduces the torque pulsations present when Hall sensor position feedback alone is used and eliminates the need for high-resolution rotor angle sensors. The proposed control strategy is applied to a slotless PMSM drive system and implemented using a digital signal processor (DSP). Experiments are carried out for the system and the results demonstrate the effectiveness of the control.

This paper discusses the problems of current decoupling control and controller tuning associated with sensorless vector-controlled induction-motor (IM) drives. In field-oriented control, the d-q synchronous-frame currents should be regulated to have independent dynamics such that the torque production of the IM resembles that of a separately excited dc motor. However, these currents are not naturally decoupled, and decoupling compensators should be used. Current loop tuning is an additional problem, since controller gains obtained by theoretical methods or simulation, quite often, do not work well on the real system. This paper proposes a new approach for current control that uses integral-sliding-mode (ISM) controllers to achieve decoupling. The synchronous-frame control voltages are synthesized as the sum of two controller outputs: a traditional one (PI) that acts on an ideal plant model and an ISM controller. The ISM controller decouples the d-q currents and compensates the parameter variations in the current loops of the machine. Simulations and experimental tests on a 0.25-hp three-phase induction machine show satisfactory results.

Due to the drawbacks associated with the use of rotor position sensors in permanent-magnet synchronous motor (PMSM) drives, there has been significant interest in the so-called rotor position sensorless drive. Rotor position sensorless control of the PMSM typically requires knowledge of the PMSM structure and parameters, which in some situations are not readily available or may be difficult to obtain. Due to this limitation, an alternative approach to rotor position sensorless control of the PMSM using a diagonally recurrent neural network (DRNN) is considered. The DRNN, which captures the dynamic behavior of a system, requires fewer neurons and converges quickly compared to feedforward and fully recurrent neural networks. This makes the DRNN an ideal choice for implementation in a real-time PMSM drive system. A DRNN-based neural observer, whose architecture is based on a successful model-based approach, is designed to perform the rotor position estimation on the PMSM. The advantages of this approach are discussed and experimental results of the proposed system are presented.