• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.3-5
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• 1996

A sensorless drive of induction motor has several advantage: low cost and availability in a harsh environment. Most of sensorless control schemes are based on the direct estimation of rotor speed from state observer. This study proposes a new sensorless control scheme. The proposed scheme is based on a reference model control which the error between the model and plant outputs decays to zero as time proceeds. The actuating signal is calculated from the fuzzy controller which increases the system stability and robustness. The simulation results indicate a good dynamic performance.

• 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.

• 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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• 1998.07b
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• pp.493-496
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• 1998

Several sensorless vector control methods of induction motor have been proposed, but these methods don't have the satisfying performance to the change of the rotor time constant. Therefore, this paper proposes the sensorless vector control method which estimates the rotor speed using MRAS and compensates the rotor time constant using current error feedback at the same time. This method can guarantees the accurate performance of sensorless vector control while the rotor speed and the rotor time constant are changing. This method is verified by computer simulation using SIMULINK in MATLAB.

• Journal of Power Electronics
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• v.6 no.1
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• pp.29-37
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• 2006

A sensorless control for an IPM (Interior Permanent Magnet) synchronous motor in a single piston rotary compressor is presented in this study. The rotor position is estimated from the d-axis and q-axis current errors between the real system and a motor model of the position estimator. The torque pulsation of the single piston rotary compressor is compensated to reduce speed ripples, as well as, mechanical noise and vibration. The proposed sensorless drive enables the compressor to operate at a lower speed which increases energy savings and reduces mechanical noise. It also gives high speed operations by a flux weakening control for rapid air-cooling and heating of the heat pump air-conditioners.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1166-1176
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• 2017

Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.