• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.3
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• pp.117-126
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• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.67-72
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• 1998

To improve control performance, especially positioning speed, of a pneumatic positioning system, dynamic characteristics of a control valve should be considered. In case we design controller including dynamic characteristics of a control valve, it's not easy to design controller gain using simple state feedback because degree of a control system is increased. This study designed controller using loop shaping of $H_{\infty}$ control theory for a model composed of a pneumatic actuator and a control valve, and positioning experiment using this controller was performed. As a result, it was verified that the controller is useful for high speed positioning of a pneumatic positioning system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.377-382
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• 1993

The low speed control of a servo motor using instantaneous speed detection method is described. To estimate the instantaneous speed from the average speed, the speed estimator of the first or second order is used. We confirm that these estimatorsimprove the speed control performance of a servo system with experiments.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.163-165
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• 2006

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK amd dSPACE DSl104 R&D board. The estimation of rotor flux linkage and rotor speed is carried out using model reference adaptive system(MRAS) method. Estimated rotor speed is used to speed controller of induction motor. Simulation results are presented to confirm speed sensorless vector control algorithm.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1069-1070
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• 2006

This study is concerned with the control system design using Labview Simulation Interface Toolkit and Matlab/simulink combined system for an application to the personal rapid transit system which has very short headway, requiring accurate speed control to avoid the impact between the vehicles. A simple equation of motion for a vehicle which is activated on the linear motor is introduced. A speed profile that should be tracked by a rear vehicle is produced based on the state information of the two vehicles(the preceding vehicle and the rear vehicle). The speed profile tracking control system is designed by Matlab/simulink. The simulation results show that the proposed control system is effective to evaluate the speed tracking performance.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.396-403
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• 1992

In order to operate a combine harvester at the optimum conditions and maximum performance, a forward speed control system(FSCS) was designed and develped. The FSCS consisted of engine, continuously variable V-belt transmission, threshing unit, traveling unit, detecting unit, and controller. Each components of the system were mathematically modeled. By a computer simulation, the effects of control parameters such as hydraulic piston speed, speed ratio, dead band of engine speed on the system performance were analysed, and the optimum control conditions were identified. The system appeared to be the most stable at the hydraulic piston speed of 10.6mm/s and the speed ratio of 0.4. The proper dead band of engine speed appeared to be 30rpm through the simulation and verification tests.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.6
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• pp.102-109
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• 2000

In this industrial induction motor speed and torque controlled drive system, the closed loop control usually requires the measurement of speed or position of amotor. However a sensorless drive of an induction motor has several advantages ; low cost and mechanical simplicity. Thus this paper investigates a field oriented control method without speed and flux sensors. The proposed control strategy is based on the Model Reference Adaptive System(MRAS) using a new flux estimator which replaces integrators with two lag circuits as the reference model. This algorithm may overcome several shortages of conventional MRAS such as integrator problems, small EMF at low speed. The simulation and experimental results indicate good speed responses.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.16 no.4
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• pp.50-59
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• 1992

The paper presents a digital speed control approach of induction motor systems by using a digital servo control method and a well-known second order differential equation as model. The basic concept of using the modeling equation stated in the above is induced from the control theory stand point such that we can describe usually the motor system connected by inverter, generator and load etc, just as a mechanical system to be controlled. The concept does not demand us the complicated vector-based modeling equation adopted in the traditional methods for the speed control of induction motor. Futhermore, the proposed speed control system can be treated as a single input and single output system. The effectiveness of the servo control system obtained by the above-mentioned design concept is illustrated by the experimental results in the presence of both step reference changes and load variations. It is observed from the experimental results that the steady state-error of the experimental set up becomes zero after some regulation time and the induction motor system is robust in spite of reference signal changes and load variations.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.138-143
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• 2011

Electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending energy between motor blocks and traction motors. Currently, switched reluctance motors have been studied because the efficient is higher than induction motors. In this paper, model of the switched reluctance motor is presented and the PID controller is applied to the model for the speed control by using Simulink. Asymmetry converter is used for real-time control and system performance is demonstrated by simulating the speed of switched reluctance motor including PID controller.