• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.510-513
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• 1996

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification at the beginning of the transient state. And an adaptive flux observer is used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verity the validity of the proposed algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.81-90
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• 2002

This paper presents an Implementation of digital high-performance position sensorless control system of Reluctance Synchronous Motor(RSM) drives with Direct Torque Control(DTC). The system consists of stator flux observer, speed and torque estimator, two digital hysteresis controllers, an optimal switching look-up table, Insulated Gate Bipolar Transistor(IGBT) voltage source inverter, and TMS320C31 DSP board. The stator flux observer Is based on the combined voltage and current model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. In order to prove the suggested sensorless control algorithm for industrial field application, we have some simulation and actual experiment at low and high speed range. The developed high-performance speed control by fully digital system are shown a good response characteristic of control results and high performance features using 1.0[kW] RSM having 2.57 reluctance ratio of $L_d/L_q$.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2113-2116
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• 1997

The speed sensorless vector control of induction motor using the rotor speed and flux estimation is widely used. In practice, these schemes depend on the accurate parameters of the machine. If in the vector control scheme an inaccurate parameter of induction motor due to skin effects and to temperature variations is used. it is difficult to achieve correct field orientation. From this reason. we propose robust speed sensorless vector control of induction motor against the variations of parameter and disturbance by using extended Kalman filter. For speed and rotor flux estimation. conventional adaptive flux observer is applied. extended Kalman filter which is correctly capable of estimating rotor flux and load by eliminating virtually influences of structural noises is proposed. Simulation results show the effectiveness of the control strategy proposed here for the induction motor drives.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.58-66
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• 1996

An adaptive input-output linearization technique of an interior permanent magnet synchronous motor with a specified output dynamic performance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive technique where the stator resistance and the magnitude of flux linkage can be estimated with the current dynamic model and state observer. Using these estimated parameters, the linearizing control inputs are calculated. With these control inputs, the input-output linearization is performed and the load torque is estimated. The adaptation laws are derived by the Popov's hyperstability theory and the positivity concept. The robustness and the output dynamic performance of the proposed control scheme are verified through the computer simulations.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.188-191
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• 2002

This paper presents a method for on-line estimation of rotor time constant of induction motor. The proposed method applies a model reference adaptive system(MRAS) using rotor flux vector. The MRAS consists of two independent observers to estimate the rotor flux vector; one based on voltage equations of rotor flux vector, the other based on current equations of them. The MRAS utilizes concept of auxiliary variables to normalize observer output and decrease high-frequency components of its input. Experimental results verify the validity and usefulness of proposed method

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1165-1168
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• 2001

The effect of sensor faults in DTC based induction motor drives is analyzed and a fault detection problem is treated. An adaptive gain scheduling observer is proposed for the design of DTC controller and a fault detection system. The observer provides not only the estimate of stator flux, a key variable in DTC system, but also the estimates of stator current, rotor speed that are useful for fault detection purpose. Simulations for various type of sensor faults are performed to evaluate the performance of the overall control system and the proposed sensor fault detection scheme.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1030-1032
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• 2000

Direct torque control algorithm for 3-level inverter-fed induction motors is proposed. Conventional selection method of the stator voltage vector shows problems of stator flux drooping phenomenon and undesirable torque control appeared especially at the low, speed operation. To overcome these problems, a proposed method uses intermediate voltage vectors, which are inherently generated in 3-level inverters. An adaptive observer is also employed to estimate some state-variables and motor parameters, which takes a deep effect on the performance of the low speed operation. Simulation and experiment results verify effectiveness of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1102-1104
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• 2000

Recently effective system-on-a-chip design methodology is developed, and ASIC chip design is much studied for motor control. This paper investigates the design and implementation of ASIC chip for sensorless speed control of induction motor using VHDL which is a standarded hardware description language. The sensorless control strategy is to design an adaptive state observer for flux estimation and to estimate the rotor speed from the estimated rotor flux and stator current. The presented system is implemented using a simple electronic circuit based on FPGA.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.3
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• pp.124-130
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• 1999

Speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of motor. Various control algorithms have been proposed for the elimination of speed senor. This paper investigates a novel speed sensorless control of induction motor. The proposed control strategy is based on MRAS(Model Reference Adaptive System) using state observer as a reference model for flux estimation. This algorithm may overcome several shortages of conventional MRAS: integrator problems, small EMF at low speed and relatively large sensitivity to resistance variation. The proposed algorithm is verified through simulation and experiment.