• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1453-1455
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• 2005

This paper presents self tuning PI controller of IPMSM drive using neural network. Self tuning PI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.9
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• pp.706-715
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• 2014

Recently, the medical community has been enthusiastically welcoming robots that are able to provide high-quality medical services across the board, including assisting the surgeons during surgeries. In response, many higher education institutions and research facilities started to conduct various experiments and studies about these robots. During such research, it was discovered that the arm of one particular robot type that is being developed to assist surgeries are prone to vibrate even from the weakest impact, in addition to other residual vibration problems. We attempted to reduce such dynamic response by using a MF-TMD that is produced by adding magnetic fluid to ECD. We verified the MF-TMD's performance by testing it within various frequency bands and attenuations. We then designed a cantilever that was structurally similar to the robot's arm. We attached the MF-TMD to this cantilever and conducted a pilot experiment, which validated our hypothesis that MF-TMD will reduce the robot arm's vibrations through its optimal damping ratio. Henceforth, we attached the MF-TMD to the robot arm in question and conducted a performance experiment in which we tuned the MF-TMD's frequency and damping factor to its optimal level and measured the vibrations of the arm. The experiment demonstrated that the vibrations that occurred whenever the arms rotated were significantly reduced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.830-836
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• 2006

In this paper described an auto tuning neuro-fuzzy PID controller based neural network. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. In this paper will design to take advantage of neural network fuzzy theory and pid controller auto toning technique. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. This controller simple structure and computational complexity are less, and also application is easy and performance is excellent in system that is strong and has nonlinearity to system dynamic behaviour change or disturbance. Finally, the proposed auto tuning neuro-fuzzy controller is applied to magnetic levitation. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.211-214
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• 1997

This paper applies fuzzy self-tuning PID controller in DS/CDMA cellular system. Power control is essential in DS/CDMA to compensate for the differing received powers due to both the slowly varying long-term and fast varying short-term fading processes and co-channel interference. The controller proposed is adaptable for the variations of the system dynamics and especially for the variable time delay which exists in mobile radio systems. Accordingly the results is the smaller power control error, that is, the smaller average transmitting power of mobile compared with the conventional control schemes. Because interferences to the other mobiles are reduced, the capacity of CDMA can be increased.

• ICROS
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• v.3 no.5
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• pp.38-42
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• 1997

본 고에서는 적응제어의 설계 기법의 연구 현황에 대해 살펴보았다. 매개변수 추정을 기반으로 적응제어기 설계 기법(Estimation-based Design Technique)은 자기동조제어를 시작으로 적응 최적제어 단계를 거쳐, 현재 다변수 적응예측제어로 발전하였고, 이는 화학공정 등 실제 플랜트에 응용될 가능성이 가장 높은 실용적인 설계기법으로 평가받고 있다. 그러나 비선형 시스템에 대한 적용 연구는 활발하지 못한 형편이다. 한편, 안정도 이론을 기반으로 적응 메카니즘을 설계하는 연구는 선형 시스템에 대한 적응제어 연구로 확장되어 현재 활발한 연구가 진행되고 있다. 앞으로 이에 대한 이론 연구가 한동안 지속될 것으로 전망된다. 그러나 이 방법은 실제 시스템에 적용시 적합한 형태로 불확실성을 모델링해야 하며 그 작업은 그리 용이하지 않을 것으로 판단된다. 그러나 부분적으로 이러한 응용연구에 대한 노력이 경주되어야 할 것이다. 비매개변수 추정방법은 적응제어 이론의 주 설계기법은 아니기 때문에 이론으로의 확장 연구는 그리 활발하지 못한 것으로 판단된다. 그러나 비교적 설계방법과 불확실성 모델링이 간단하여 실제 응용에 가장 용이하게 적용될 수 있을 것으로 생각된다.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.223-226
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• 1991

In this paper, the problem of designing on adaptive controller for dc drives using state observers, which is operated under varying load conditions, is addressed. A robust self-tuning controller that can track a constant reference and reject constant load disturbances is also studied. This scheme is very attractive since the estimates of system parameters are available in real time. Parameter estimation is based on the recursive least squares method and the control algorithm of the pole placement technique. Also, state observer systems are applied. State observer systems are required to estimate the states quickly and exactly without being affected by the disturbances.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.122-132
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• 1993

In this paper, a self tuning control algorithm is proposed for the high performance drive of DC servo motor, which is adequate to the servo system having frequent load variation. In order to realization of the algorithm, the control system is developed using a fixed point high speed digital signal processor. TMS320C25. Control algorithm is composed of two parts. One is estimation law part using recursive least mean square method, the other is control law part using minimum variance control method. For the purpose of easiness of applying adaptive algorithm, developed control system is based o PC-DSP structure which can develop, debug programs and monitor the dynamic behaviors,etc. Through computer simulation and experimental results, it was verified that proposed control system could estimate system parameters and was robust to the variation of the load and as a result, was adequate to the servo motor drives.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.5
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• pp.367-376
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• 1987

In this paper we have disigned and implemented a real time ALE (adaptive line enhancer) using a high speed digital processor,NEC 7720. For the ALE system, we have employed an adaptive LMS(least mean square) algorithm proposed by Widrow and Hoff and a 32-order FIR(finite impulse response) filter. Extensive computer simulations have been performed to investigate the peformance of the ALE and to determine necessary parameters for hardware design. The developed software for an NEC 7720 was tested in real time operation using an NEC7720 hardware emulator. The ALE has been tested by sinusoidal waves and real CW (continuous wave) signals. It was found that the experimental results were well agreed with the computer simulation results. Thus it can be concluded that the ALE is useful for detection and enhancement of a sinusoidal signal which is corrupted by an additive Gaussian noise.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2139-2142
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• 1997

The most important thing in vector control scheme is the knowledge of accurate electrical motor parameters. These parameters can computed by conventional motor test, such as no-load and locked rotor tests. However, the values from these tests are different from actual motor parameters, and the adjustment process of the parameters is time consuming. This paper presents an auto-tuning method for vector control of induction motor. The tuning algorithm is based on the rotor flux behavior of the induction motor for stepwise torque current command. The transient terminal voltage caused by the undesirable variation of the rotor flux is used for tuning the slip gain $K_5$ defined as the inverse of the rotor time constant. The electrical parameters of induction motor can also calculated by this method. The presented method is evaluated through the computer simulations.