• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1046-1049
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• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer is an adaptive gain scheduling observer where motor speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimates of stator resistance and speed are included as observer parameters. Simulation results show that the proposed flux observer gives better control and estimation results than conventional flux estimator specially in low speed region.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.7
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• pp.399-405
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• 2002

This paper presents an implementation of digital high-performance Position sensorless motion control system of an induction motor drives with Direct Torque Control(DTC). The system consist of closed loop stator flux and torque observer, speed and torque estimators, two hysteresis controller, optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP board. The stator flux observer is based on the combined current and voltage model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. The speed observer is using the model reference adaptive system(MRAS) with rotor flux linkages for speed turning signal. The simulation and experimental results are provided to evacuate the consistency and the performance of the suggested position sensorless control algorithm. The developed position sensorless system are shown a good motion control response characteristic and high performance features using 2.2[kw] general purposed induction motor.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.241-251
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• 2002

The effect of sensor faults in direct torque control(DTC) based induction motor drives is analyzed and a new Instrument fault detection isolation scheme(IFDIS) is proposed. The proposed IFDIS, which operated in real-time, detects and isolates the incipient fault(s) of speed sensor and current sensors that provide the feedback information. The scheme consists of an adaptive gain scheduling observer as a residual generator and a special sequential test logic unit. The observer provides not only the estimate of stator flux, a key variable in DTC system, but also the estimates of stator current and rotor speed that are useful for fault detection. With the test logic, the IFDIS has the functionality of fault isolation that only multiple estimator based IFDIS schemes can have. Simulation results for various type of sensor faults show the detection and isolation performance of the IFDIS and the applicability of this scheme to fault tolerant control system design.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.3
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• pp.154-160
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• 2004

In this paper, a combined field orientation and adaptive backstepping approach using a sliding mode adaptive flux observer, is proposed for the control of induction motor In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer based on a fixed stator frame model and mechanical lumped uncertainty such as inertia moment, load torque disturbance, friction compensated by the adaptive backstepping based on a field-oriented model. Simulation results are provided to verify the effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.219-223
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• 1995

This paper deals with the robust control system for parameter variations, fast responses and load torque variations. Frist, fuzzy-sliding adaptive control be used to. Fuzzy-sliding adaptive control is good at fast response. Second, there are many requests for selecting freely the moment of inertia, even though moment of inertia is determined with the materials, structure, shape, and size of the motors. Therefore we developed an inertia-lowering control system that uses torque observer to reduce the moment of inertia. Finally, using torque observer, torque control is done so as to compensate load torque. Consequently, the proposed system verified the superiority through the simulations using MATLAB.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1004-1005
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• 2006

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS (Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Simulation results are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.421-424
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• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• Journal of Power Electronics
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• v.14 no.1
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• pp.125-134
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• 2014

This paper presents a robust and speed-sensorless stator flux estimation for induction motor direct torque control. The proposed observer is based on sliding mode approach. Stator electrical equations are used in the rotor orientation reference frame to eliminate the observer dependence on rotor speed. Lyapunov's concept for systems stability is adopted to confine the observer gain. Furthermore, the sensitivity of the observer to parameter mismatch is recovered with an adaptation technique. The nonlinearities of the pulse width modulation voltage source inverter are estimated and compensated to enhance stability at low speeds. Therefore, a new method based on the model reference adaptive system is proposed. Simulation and experimental results are shown to verify the feasibility and effectiveness of the proposed algorithms.