• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2376-2384
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• 2018

To reduce the size and cost of motor driving systems, several methods for driving multiple parallel-connected motors with a single inverter have been proposed. However, dual PMSMs driven by a single inverter, unlike induction motors, have a problem with instability due to system resonance caused by disturbances such as load imbalance and tolerances between two motors. To drive dual SPMSMs fed by a single inverter, this paper proposes an active damping algorithm to effectively suppress resonance by using one-sided sensorless speed control and position difference estimation. By deriving rotor position difference from d-q current differences between two motors, the proposed method is affected less by position difference estimation errors and is simpler than dual sensorless position estimation.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.9-11
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• 1998

Most of sensorless algorithms are based on motor equations including electrical and mechanical parameters. However, parameter variation and uncertain error decrease the accuracy of speed estimation of PMSM. This paper investigates the sensorless speed control of PMSM considering parameter variation. The proposed algorithm use the speed compensator which is robust in parameter variation and error. The simulation and experimental results indicate good performances.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.873-881
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• 2014

Speed sensorless modes of operation are becoming standard solution in the area of electric drives. This paper presents flux estimator and speed estimator for the speed sensorless vector control of induction motors. The proposed sensorless methods are based on the model reference adaptive system (MRAS) observer and adaptive speed observer (ASO). The proposed speed estimation algorithm can be employed in the power control of grid connected induction generator for wind power applications. Two proposed schemes are verified through computer simulation PSIM and compared their simulation results.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.614-616
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• 2004

It is waste of time in industrial plant that the PI controller gain tuning. The PI controller has many trial-and-error steps for gain design. This paper proposes the optimum gain design of PI controller using a speed estimation in sensorless vector-control. In this method, a degree of stability and Hurwitz theory are applied and the controller gain is expressed by system parameters.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.4
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• pp.36-44
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• 1997

For high performance ac drives, the speed sensorless vector control and the stator flux orientation concept have received increasing attention. This paper describes a speed and flux sensorless vector-controlled induction machine(IM) drive based on the stator flux-oriented control. To improve the accuracy and operating range, the control system employs the previously presented speed and flux estimation methods, and then we present a developed method of estimating the speed of IM. In the proposed method all differential and integral terms have been eliminated by giving a very fast, low-cost, effective and practical alternative to the methods currently available. The effectiveness of the proposed method is verified by simulations and experimental results.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.47-48
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• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.35-41
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• 2014

This paper presents a design method of programmable low pass filter(PLPF) which reduce an estimation error of a zero crossing point(ZCP) for a high speed brushless DC(BLDC) motor drive. BLDC motor sensorless drive is possible by estimation of ZCP. The ZCP estimated by detecting a change of back-EMF polarity has the estimation error because noises exist on the measured back-EMF. Therefore a calculated commutation timing using the ZCP is inaccurate. And the inexact commutation timing leads to ripples of 3-phase current and degradation of drive performance. This paper proposes the design method of the PLPF to overcome these problems. First, a speed calculated a inaccurate period of the ZCP is analyzed in the frequency domain. Then, the PLPF that has varying cut-off frequency according to change of the speed is designed on the frequency analysis result. The proposed method is verified by the experiment.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.612-619
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• 2005

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2113-2116
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• 1997

The speed sensorless vector control of induction motor using the rotor speed and flux estimation is widely used. In practice, these schemes depend on the accurate parameters of the machine. If in the vector control scheme an inaccurate parameter of induction motor due to skin effects and to temperature variations is used. it is difficult to achieve correct field orientation. From this reason. we propose robust speed sensorless vector control of induction motor against the variations of parameter and disturbance by using extended Kalman filter. For speed and rotor flux estimation. conventional adaptive flux observer is applied. extended Kalman filter which is correctly capable of estimating rotor flux and load by eliminating virtually influences of structural noises is proposed. Simulation results show the effectiveness of the control strategy proposed here for the induction motor drives.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.503-504
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• 2015

This paper deals with the analysis of characteristics of position and speed estimator of an adaptive sensorless control algorithm for PMSM drives. The analysis shows that the back emf constant variation results in the position estimation error, but does not the speed estimation error. The simulation and experimental results are shown to verify the analysis result and the usefulness of the back emf constant estimator.