• ETRI Journal
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• v.37 no.6
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• pp.1165-1175
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• 2015

This paper presents an advanced sensorless permanent magnet (PM) brushless motor controller integrated circuit (IC) employing an automatic lead-angle compensator. The proposed IC is composed of not only a sensorless sine-wave motor controller but also an isolated gate-driver and current self-sensing circuit. The fabricated IC operates in sensorless mode using a position estimator based on a sliding mode observer and an open-loop start-up. For high efficiency PM brushless motor driving, an automatic lead-angle control algorithm is employed, which improves the efficiency of a PM brushless motor system by tracking the minimum copper loss under various load and speed conditions. The fabricated IC is evaluated experimentally using a commercial 200 W PM brushless motor and power switches. The proposed IC is successfully operated without any additional sensors, and the proposed algorithm maintains the minimum current and maximum system efficiency under $0N{\cdot}m$ to $0.8N{\cdot}m$ load conditions. The proposed IC is a feasible sensorless speed controller for various applications with a wide range of load and speed conditions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.195-200
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• 2004

Many kinds of speed sensorless control system of induction motor had been developed. But it is difficult to implement at the real system because of complex algorithm and equations. This paper investigates a novel speed sensorless control of induction motor using neural networks. The proposed control strategy is based on neural networks using stator current and output of neural model based on state observer. The errors between the stator current and the output of neural model are back-propagated to adjust the rotor speed, so that adaptive state variable will coincide with the desired state variable. This algorithm may overcome several shortages of conventional model, such as integrator problems, small EMF at low speed and relatively large sensitivity of stator resistance variation. Also, this paper presents a newly developed optimal equation about the momentum constant and the learning rate. The proposed algorithms are verified through simulation.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.103-104
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• 2011

This paper suggests a new starting and stopping method appropriate for the sensorless PMSM drive with air bearings. The proposed method based on the sensorless control algorithm of PMSM uses additional d-axis current control to cope with the limitation of the adopted back-emf based sensorless algorithm in the low speed region. The experimental results show that the proposed method drives appropriately the PMSM with air bearings.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.540-543
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• 1999

This paper describes a speed sensorless algorithm for vector control system with compensated stator resistance and rotor time constant of induction motor using a model reference adaptive system(MRAS). The system are composed of two MRAC, one is a rotor speed estimation and a stator resistor identification by back-EMF observer, other is used to identify rotor time constant by magnetizing current observer, so that the estimation can be cover a very low speed range with a robust control. The suggest control strategy and estimation method have been validated by simulation study. In the simulation using Matlab/Simulik, the proposed speed sensorless vector control system are shown to operate very well in spite of variable rotor time constant and load fluctuation.

• Journal of Power System Engineering
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• v.18 no.5
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.69-76
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• 2009

This paper describes sensorless high-speed control for 45,000rpm/22kw type PMSM by using iterative adaptive sliding mode observer. The proposed algorithm is based on sensorless vector control by on-line estimating the speed of rotor in the wide speed operating range between the starting operation. In addition, it shows the enhanced performance of the iterative adaptive observer by lessening its chattering and getting stable response in limited PWM period. The simulation and experiment results show the reliable performance of the proposed algorithm through starting to high speed operating range.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.96-102
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• 1999

Sensorless speed estimation in induction motor systems is one of the most control engineers. Based on the estimated speed the vector control has been applied to the high precision torque control however most speed estimation methods use adaptive scheme so that it takes long time to estimate the speed. Thus the adaptive estimation scheme is not effective to the induction motor which requires short sampling time. In this paper a new linearized equation of induction motor system is proposed and a sensorless speed estimation algorithm based on observation techniques is developed. First the nonlinear induction motor equation is linearized at an equilibrium point. Second a proportional integral(PI) observer is applied to estimate the speed state in the induction motor system. Finally simulation results will assure the effectiveness of the new linearized equation and the sensorless estimation algorithm by using PI observer in the nonlinear induction motor system.

• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.178-181
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• 2003

This paper presents a position sensorless control system of Switched Reluctance Motor(SRM) using Neural Network. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase currents and rotor position. A sufficient experimental data was used for neural network training. The proposed position sensorless control system was realized using TMS320F240 DSP. The experimental result shows some good results, and verifies the possibility of this algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.107-115
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• 2006

In this paper, a new speed sensorless control based on an instantaneous reactive power is proposed for the interior permanent magnet synchronous motor(IPMSM) drives. In proposed algorithm, the current observer estimates the line currents and the estimated speed can be yielded from the voltage equation because the information of speed is included in back EMF. To implement speed sensorless control, the current observer is composed by using the voltage equation of the IPMSM in the stationary reference frame fixed to the stator. The estimated speed of the rotor is composed by using the voltage equation of the IPMSM in the rotating reference frame fixed to the rotor The estimated speeds to minimize the speed error compensated by using the instantaneous reactive power. The instantaneous reactive power is calculated on the rotating reference frame fixed to the rotor. The effectiveness of the preposed algorithm is confirmed by the experiments.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.112-114
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• 1997

Recently sensorless PMSM is much studied for the industrial applications and home appliances. Most of sensorless algorithm are based on the motor equations of which coefficients are motor parameters. However, uncertainty of motor parameter effects the accuracy of speed estimation of PMSM. This paper investigates the robust speed control of sensorless PMSM which has robustness to parameter uncertainty or variation. The parameter compensation is performed through PI control of the speed error between the estimated speed and the real speed obtained from the measured current. The proposed algorithm is verified through the experiment.