• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.1
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• pp.52-58
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• 2003

The application of a sliding mode control for improving the dynamic response of an induction motor based speed control system is presented in this paper and provides attractive features, such as fast response, good transient performance, and insensitivity to variations in plant parameters and external disturbance. However, chattering is a difficult problem for which the sliding mode control is a popular solution. This paper presents a new fuzzy-sliding mode controller for a sensorless vector-controlled induction motor servo system to practically eliminate the chattering problem for traction applications. A DSP based implementation of the speed control system is employed. Experimental results are presented using a propulsion system simulator. The performance of the drive is shown to be practically free from chattering.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.962-963
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• 2015

This paper proposes a sensorless V/f control method of the interior mounted permanent magnet synchronous motor without damper winding. Arithmetic computation is simpler than vector control. And the lower cost price, dynamics and stability is guaranteed. When the loss of synchronization occurs with the load disturbances, the stability loop with a reduced order observer is applied quickly and accurately to improve the speed error.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2107-2109
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• 1997

Speed sensors are required for the vector control of induction motors. These sensors reduce the sturdiness of the system and make it expensive. Therefore, a drive system without speed sensors is required. Also, the rotor inertia constant, the damping constant and the disturbed load torque of the IM are estimated by the RLS estimator and a torque observer. Then the observed disturbance torque is fed forward to increase the robustness of the IM speed drive.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.467-470
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• 2002

Internet provides the useful method to monitor the current states of the machine tool no matter where a personnel is monitoring them. In this paper, a monitoring method of the torque of the machine tool's spindle induction motor using internet is suggested. The torque of vector controlled induction motor is estimated without speed measuring sensor. Only stator currents are measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. Graphical programming is used to implement the suggested algorithm, to monitor the torque of an induction motor in real time and to make the estimated torque monitored on client computers. To solve the fluctuation problem of estimated torque caused from instantly varying rotating speed of an induction motor, the rotating speed is reconstructed based on the measured current signals. Mechanical part of the machine tool is also reconstructed using the data obtained from preliminary experiments. Torque of the spindle induction motor is well monitored on the client computers with 3% error range under various cutting conditions.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.175-177
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• 2005

An interior permanent magnet synchronous motor (IPMSM) is receiving increased attention for many industrial applications because of its high torque to inertia ratio, superior power density, and high efficiency. This paper presents algorithm for speed sensorless vector control based on a fuzzy controller and an instantaneous reactive power. Effectiveness of algorithm is confirmed by the experiments.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.260-262
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• 1998

A new method of induction motor drive, which requires not shaft encoder, is presented. This system has both torque and speed controls that are performed by vector control. The scheme is on the basis of a rotor flux speed control, which is performed by torque producing current and rotor flux, derived from the stator voltages and currents. But, there is a problem with respect to the calculated rotor flux vector, which is an integrating operation by which the rotor induced voltage is converted into the rotor flux. The calculated rotor flux does not work so that it is unstable in initial operation, as motor speed approaches zero. For the proposed rotor flux estimator, a lag circuit is employed, to which both the motor-induced voltage and rotor flux command are imposed, and it is possible to calculate even a low frequency down to standstill. We show the validity of the proposed control method through several computer simulations.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.2
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• pp.91-102
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• 1999

The paper describes a robust adaptive control algorithm for induction motor drive without speed sensor at low speed range. The control algorithm use only current sensors in a space vector pulse width modulation within loop control with rotor speed estimation and voltage source inverter. On-line rotor speed estimation is based on utilizing parallel model reference adaptive control system. MRAC of the modified flux model for flux and rotor speed estimator uses dual-adaptation mechanism, ${\omega}_r$ and ${\omega}_e$ scheme. The estimated flux components in the model can be compensated from the effects of offset errors on pure integrals. It can be compensated to the parameter variations and torque fluctuation with speed estimation in less then 10 rad/sec. In a simulation, the proposed induction motor control algorithm without speed sensor at very low speed range are shown to operate very well in spite of variable rotor time constant and fluctuating load without change the controller parameters. The suggested control strategy and estimation method have been validated by simulation study, and it proposed the designed system for the implementation using TI320C31 DSP/ASIC controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1478-1481
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• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network controller. The back-propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back-propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1274-1285
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• 2015

This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.

• Journal of IKEEE
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• v.24 no.4
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• pp.954-960
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• 2020

This paper proposes a speed variable proportional resonant current control method for a single-phase permanent magnet synchronous motor(PMSM). Due to the electromagnetic characteristics of a single-phase PMSM, negative and zero torques are generated in the part corresponding to the phase difference between the stator current and the back electromotive force. In addition, overcurrent limitation is required because of the low stator resistance and inductance in sensorless operation. When using the vector control for current control of single-phase PMSM under these conditions, processes of coordinate transformation, inverse coordinate transformation, and generation of virtual dq-axis components are required. However, the proposed variable speed proportional resonant current control method does not need the coordinate transformation used for AC motors. In this paper, we have confirmed stable maneuverability by using variable proportional resonant current control algorithm, and proposed sensorless control based on a mathematical model of a single-phase PMSM without a position sensor when reaching a constant speed. The usefulness of the current control method was verified through several experiments.