• Journal of Electrical Engineering and Technology
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• 제12권3호
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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.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.17-19
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• 2005

This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using learning mechanism-fuzzy neural network(LM-FNN) and artificial neural network (ANN) control. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid Intelligent control

• 전기학회논문지P
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• 제61권4호
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• pp.199-205
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• 2012

This paper propose a improved parameter estimations of five-phase squirrel-cage induction motor(IM) for speed control system on field oriented control(FOC). In order to high performance control of ac the motors using a FOC and DTC(direct torque control) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, rotor position and speed estimation, and so on. We are suggest a estimation method of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental. There are results of stator winding test, no-load test, locked rotor test, and obtained equivalent circuits using manufactured experimental apparatus. For presenting the superior performance of the speed control system in adapted the parameters, experimental results are presented using a 32-bit fixed point TMS320F2812 DSP with 1.5[KW] IM.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.808-810
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• 1996

In this paper, neural network, which has learning capability, is used for fault type classification and fault section estimation for high speed relaying. The potential of the neural network approach is demonstrated by simulation using ATP. The instantaneous values of voltages and currents are used the inputs of neural networks. This approach determines the fault section directly. In this paper, back-propagation network(BPN) is used for fault type classification and fault section estimation and can use for high speed relaying because it determines fault section within a few msec.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2014년도 전력전자학술대회 논문집
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• pp.114-115
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• 2014

This paper proposes a new speed and position estimation method for PMSM(Permanent Magnet Synchronous Motor) using low-resolution hall-effect sensors. In general, there are a variety of sensors to estimate rotor position for PMSM such as resolvers, and encoders. Position detection using hall-effect sensors that detect the flux of the rotor for rotor position is excellent method in terms of cost and space, but has low-resolution. To overcome this problem, this paper proposes a new speed and position estimation observer. The performance of the observer has been verified by simulations carried out using Matlab/Simulink.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권3호
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• pp.145-153
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• 2004

A nonlinear adaptive speed observer is designed for the sensorless control of induction motors. In order to design the speed observer, the measurements of the stator currents and the estimates of the rotor fluxes are used. The sliding mode cascade observer is designed to estimate the time derivatives of the stator currents. The open-loop observer is designed to estimate the rotor fluxes and its time derivatives using the stator current derivatives. The adaptive observer is also designed to estimate the rotor resistance. Sequentially, the rotor speed is calculated using these estimated values. It is shown that the estimation errors of the corresponding states and the parameters converge to the specified residual set. It is also shown that the speed controller using these estimates is performed well. The simulation examples are represented to investigate the validity of the proposed observers for the sensorless control of induction motors.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.140-142
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• 2007

This paper presents an effective method of precise velocity control at low speed with a low resolution encoder. Multirate observer to estimate the velocity at every DSP control period is used except a constant velocity mode. The observer corrects the estimation error when detects pulse signal. Unlike the conventional methods, the multirate estimator is stable at a low speed. However, the multirate estimator shows ripples at a constant velocity. Thus, in this paper we use a velocity prediction method which uses the present velocity from the previous average velocity to reject the ripple. In a summary, at a constant speed mode, the predicted velocity is used. Otherwise, the estimated velocity by the multirate obvserver is used. The effectiveness of the multirate observer and ripple rejection at low speed is verified through various simulations.

• Journal of Advanced Marine Engineering and Technology
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• 제28권2호
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• pp.185-191
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• 2004

This study describes the scheme of vector drive system without speed sensor for AC servo motor using theory of a flux observer and based on the field oriented vector control. The new method of speed estimation is presented from operate with the position and magnitude of the secondary flux which obtain from the voltage reference and detected current. As the estimated speed is settled by the flux and the machine-specific parameters. this method don't need to adjust the gain of the parameter. Based on the derived theory for vector control. the scheme for sensorless vector drive of AC servo motor is designed and realized. And the experiment verifies it passable to realize the sensorless vector drive based on a field-oriented type.