• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.366-368
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• 1994

This paper deals with the vector control that control of torque and speed of the induction motor using field-oriented control method. Rotor flux is estimated using the indirect sensing method based on the rotor circuit equation in the synchronously rotation reference frame, and slip angle and rotor position are caculated from rotor angular velocity and stator current. Through modeling and digital simulation with a voltage source inverter, it is shown that the proposed scheme gives good static and dynamic performance to the induction motor drive.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.294-296
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• 1995

In this paper, a vector control method for a AC-Excited BLSM(Brushless Synchronous Motor) is proposed. The BLSM has a feature that separate exciter is not needed for excitation. The proposed method is described in two parts as follow, one is the design of drive and the other is a modeling for its implementation. Rotor flux is estimated using indirect sensing method based on voltage equation in the synchronously rotation reference frame. And rotor position is calculated from rotor angular velocity and stator current. Through computer simulation results of this proposed system, it is shown that the BLSM drive has a ability of precision torque control from the static and dynamic performance.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1218-1220
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• 1992

This paper presents the three section sliding mode control algorithm based on variable structure current controller design in a synchronous frame and indirect field oriented control method, and applies it to the position control of induction motor. This control scheme solves the problem of robustness loss during the reaching phase that occurs in a conventional VSC strategy, and ensures the stable sliding mode and robustness enhancement throughout an entire response. As the performance of a VSI fed induction motor drives depends on the characteristics of inner loop current controller, it is desired that the current controller have the fast tracking and robust nature. Therefore, we introduced the voltage mapping table based on the concept of voltage space vector for variable structure current control, and implemented fully digital control system using 16-bit microcontroller with on-chip peripherals without additional processing circuits. Simulation and experimental results confirm the validity of this control scheme for robust AC servo drive system of VSI fed induction motor.

• Journal of Power Electronics
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• v.9 no.3
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• pp.481-490
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• 2009

This paper describes a SVPWM overmodulation scheme of NPC type three-level inverter for traction drives which extends the modulation index from MI=0.907 to unity. SVPWM strategy is organized by two operation modes of under-modulation and over-modulation. The switching states under the under-modulation modes are determined by dividing them with two linear regions and one hybrid region the same as the conventional three-level inverter. On the other hand, under the over-modulation mode, they are generated by doing it with two over-modulation regions the same as the conventional over-modulation strategy of a two level inverter. Following the description of over-modulation scheme of a three-level inverter, the system description of a vector controlled induction motor for traction drives has been discussed. Finally, the validity of the proposed modulation algorithm has been verified through simulation and experimental results.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1141-1143
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• 2001

This paper presents a detailed study of the reduced-model extended Kalman filter(EKF) for estimating the rotor speed of an induction motor drive. The general structure of the Kalman filter is reviewed and the various system vectors and matrices are defined. By including the rotor speed as a state variable, the EKF equations are established from a discrete two axis model of the three-phase induction motor, using the software MATLAB/Simulink, simulation of the EKF speed estimation algorithm is carried out for an induction motor drive with indirect vector control.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.5-162
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• 2001

This paper presents a indirect vector control system for induction motors using an adaptive fuzzy logic(AFL) speed estimator. The proposed speed estimator is based on the MRAS(Mode Referece Adaptive System) scheme. In general, the MRAS speed estimation approaches are more simple than any other strategies. However, there are some difficulties in the scheme, which are strong sensitivity to the motor parameters variations and necessity to detune the estimator gains caused by different speed area. In this paper, the AFL speed estimator is proposed to solve the problems. The structure of the proposed AFL is very simple. The input of the AFL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed. Moreover, the back propagation algorithm is combined to adjust the parameters of the fuzzy logic to the most appropriate values during the operating the system. Finally, the validity of the ...

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.10
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• pp.443-445
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• 2006

Generally PI controller is used to control the speed of an induction motor. It has the good performance of speed control in case of adjusting the control parameters. But it occurred the problem to change the control parameters in the change of operation condition. In order to solve this problem, Fuzzy control or Artificial neural network is introduced in the speed control of an induction motor. However, Fuzzy control have the problems as the difficulties to change the membership function and fuzzy rule and the remaining error Also Neural network has the problem as the difficulties to analyze the behavior of inner part. Therefore, the study on the combination of two controller is proceeded. In this paper, Fuzzy-neural controller to make up these controllers in parallel is proposed and the speed control of an induction motor is performed using the proposed controller Through the experiment, the fast response and good stability of the proposed speed controller is proved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1289-1301
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• 2011

In this paper, flux estimation method at the Induction motor is applied to stability flux estimate of possibility in overall speed domain. angle operation has voltage and current and speed information using the Induction motor direct control method. Induction motor direct control is material to flux information. Exact flux estimation method to using current model flux estimator of low-speed domain and voltage model flux estimator of high-speed domain. Speed and current and flux controller using PI controller. And error of integral requital for add to Anti-Windup PI controller. Verified to performance of Current model Flux controller and voltage model flux controller using Matlab / Simulink. Analysis has parameter influence of direct vector control and indirect vector control at the Induction motor vector control. So, verified to minute control. Analyzed to simulation result and proof to validity of presented algorithm.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.87-93
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• 2002

This paper is presented new fuzzy controller for high performance of induction motor drive. New fuzzy controller took out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller was motivated by the problems of direct fuzzy controller. The direct controller was given generally inevitable overshoot when one tries to reduce rise time of response. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in provide a thorough comparative insight into the behavior of induction motor drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by the simulation results for induction motor drive system.