• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2585-2588
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• 2003

2 관성 공진계는 마른 응답을 위해 제어이득을 크게 하면 공진에 의해 축비틀림 진동이 일어나는 경우가 많다. 본 논문에서는 반복 학습 제어기법을 활용하여 불확실한 모델 계수를 포함하는 2 관성 공진계의 진동억제를 시도한다. 2관성 공진계의 경우 제어 대상이 되는 부하측 속도는 학습 제어로 직접 적용하기가 힘들고 또한 측정 또한 어렵다. 본 논문에서는 부하측 속도와 전동기측 속도간의 관계를 이용하여 직접 부하측 속도를 제어하는 대신 전동기측 속도를 제어하여 간접적으로 부하측 속도를 제어하였다. 제안된 방식은 전형적인 2 관성 공진계에 모의 실험을 통해 적용되었고, 정확한 모델이 없이도 진동 없는 마른 응답특성을 보여준다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.137-140
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• 2003

2관성 공진계는 전동기와 부하 사이에 탄성이 있는 동력 전달 체계를 포함하는 시스템으로 고속 제어시 진동이 발생된다. 이와 같은 2관성 공진계에 대해 궁극적인 출력이 되는 부하의 위치 및 속도는 측정하기가 어렵다. 이에 기존의 연구들은 추정기등을 이용하여 부하의 속도를 추정하여 이를 제어에 활용하는 방식으로 구성되어진다. 그러나 이와 같이 추정기를 사용하기 위해서는 정확한 모델이 필요하다. 본 논문에서는 다소 부정확 모델에 대해서도 매우 정교한 제어 성능을 갖는 반복 학습 제어를 이용하여 2관성 공진계의 위치 제어를 시도하고자 한다. 제시된 방법은 2관성 공진계에 대한 모델링이 정확하지 않더라도 진동 없이 정확한 위치 제어가 가능하다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.693-698
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• 2004

In this paper, an iterative learning control method is applied to suppress a vibration of a 2-mass system which has a flexible coupling between a load and a motor. More specifically, conditions for the load speed without vibration are derived based on the steady-state condition. And the desired motor position trajectory is synthesized based on the relation between the load and motor speed. Finally, a PD-type iterative learning control law is applied for the desired motor position trajectory. Since the learning law applied for the desired trajectory guarantees the perfect tracking performance, the resulting load speed shows no vibration even when there exist model uncertainties. A modification to the learning law is also Presented to suppress undesired effects of an initial position error, The simulation results show the effectiveness of the proposed learning method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.4
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• pp.36-44
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• 2003

In the industrial motor drive system which is composed of a motor and load connected with a flexible shaft, a torsional vibration is often generated because of the elastic elements in torque transmission. To solve this problem, the two degrees of freedom H$_{\infty}$ controller was designed. But it is difficult to realize that controller. In this paper, H$_{\infty}$ control of 2-mass system using partial state feedback and resonance ratio control is proposed. Proposed controller has simple structure but satisfies the attenuation of disturbances and vibrations.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.332-335
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• 1997

In the industrial motor drive system, a shift torsional vibration si often generated when a motor and a load are connected with a flexible shaft. This paper treats the vibration suppression control of such a system. In this paper, the state feedback controller of the two-mass resonant system using the H$\infty$ filter is proposed. The H$\infty$ filter is robust in noise and disturbance. Simulation results show the validity proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.42-46
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• 2004

A 2-mass resonant system is one that has a flexible coupling between a load and a driving motor. Due to this flexibility, the system often suffers vibration especially when the motor is controlled for higher speed command. In order to suppress such a vibration, an iterative learning control is applied to the 2-mass resonant system in this paper. The motor speed is controlled according to the relation with the load speed. The desired speed trajectories are derived under the condition for no vibration. The simulation result suggests that the proposed method effectively suppresses the vibration even when there exist model uncertainties.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.307-310
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• 2003

In this paper, an iterative learning control method is applied to suppress the vibration of a 2-mass system which has a flexible coupling between a load an a motor. More specifically, conditions for the load speed without vibration are derived based on the steady-state condition. And the desired motor position trajectory is synthesized based on the relation between the load and motor speed. Finally, a PD-type learning iterative control law is applied for the desired motor position trajectory. Since the learning law applied for the desired trajectory guarantees the perfect tracking performance, the resulting load speed shows no vibration. In order to handle the initial position error, the PD-type learning law is changed to PID-type and a weight function is added to suppress the residual vibration caused by the initial error. The simulation results show the effectiveness of the proposed learning method.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.123-126
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• 2003

This paper presents an speed reference trajectory planning methods for vibration suppression in a t-mass resonant system which has a flexible coupling between a load and a driving motor. Due to this flexibility, the system often suffers vibration especially when the motor is controlled for higher speed command. The steady state conditions are utilized to derive desired load speed trajectory which does not cause the torsional vibration. And the desired motor speed trajectory is synthesized base on the relation between load and motor speed. The simulation and experiment result suggest that the proposed method effectively suppress the vibration.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.515-517
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• 1997

In the industrial motor drive system, a shaft torsional vibration is often generated when a motor and a load are connected with a flexible shaft. This paper treats the vibration suppression control of such a system. In this paper, two-degree-of-freedom(TDOF) control of the two-mass resonant system using the $H_{\infty}$ filter is proposed. TDOF control method satisfies the command following property and the internal stability at the same. The $H_{\infty}$ filter is robust in noise and disturbance. Simulation results show the validity of the proposed control method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.286-293
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• 1999

A new control scheme using a torsional torque estimator based on a neural network is proposed and investigated for improving control characteristics of the high-performance motion control system. This control method presents better performance in the corresponding speed vibration response, compared with the disturbance observer-based control method. This result comes from the fact that the proposed neural network estimator keeps the self-learning capability, whereas the disturbance observer-based torque estimator with low pass filter should dbjust the time constant of the adopted filter according to the natural resonance frequency detemined by considering the system parameters varied. The simulation results shows the validity of the proposed control scheme.