• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1634-1635
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• 2007

본 논문은 갠트리 크레인의 시뮬레이터를 제작하여 적응형 흔들림 제어기를 설계한다. 흔들림 감지는 디지털 카메라 센서를 이용하였으며 모델기반 적응제어를 이용하여 제어규칙을 산출한다. 제어규칙은 리아푸노브 안정성이론을 적용하였으며 정의된 리아푸노브 함수의 미분식이 음수를 갖기 위한 크레인의 적응형 제어입력을 계산한다. 제안한 제어기의 성능을 검토하기 위하여 실시간 제어실험을 실시하였으며 이송체의 무게 변화에 대한 적응성을 검토한다. 또한 기존의 PI 제어기도 함께 실험하여 성능의 비교 검토한다.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.556-557
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• 2014

This paper presents an artificial intelligence - Deep Belief Network (DBN) gain-scheduling adaptive PI controller scheme for dual active bridge (DAB) converter. The PI gains are allowed to vary within a predetermined range and therefore eliminate the problems faced by the conventional PI controller. The performance of the proposed controller is simulated and compared with the conventional fixed PI controller under various conditions. The experimental prototype of the DAB converter is implemented using a digital signal processor of TMS320F28335 manufactured by Texas Instrument to examine and to evaluate the performance criteria of the proposed controller. Simulation and experimental results show improvements in transient as well as steady state responses of the proposed controller over the conventional fixed PI controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2234-2241
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• 1993

The torque variation in drilling process represents the problems of the efficient and stable machining. In order to cope with them, the active control method is adopted to drill the workpiece under the constant cutting torque though the cutting stiffness of the workpiece or the diameter of the drill bit changes. The cutting process is modeled in the geometric viewpoint related with the feed and the number of cutting lips. And the dynamic model is approximated to the first order system for the purpose of control. The adaptive PI control is used in computer simulations and experiments. The results of the study show the validity of the drilling method with torque control.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.833-844
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• 1995

In self-tuning predictive control algorithm for steam generator is presented. The control algorithm is derived by suitably modifying the generalized predictive control algorithm. The main feature of the unposed method relies on considering the measurable disturbance and a simple adaptive scheme for obtaining the controller gain when the parameters of the plant are unknown. This feature makes the proposed approach particularly appealing for water level control of steam generator when measurable disturbance is used. In order to evaluate the performance of the proposed algorithm, computer simulations are done for an PWR steam generator model. Simulation result show satisfactory performances against load variations and steam flow rate estimation errors. It can be also observed that the proposed algorithm exhibit better responses than a conventional PI controller.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.542-544
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• 2020

최근 분산전원 시스템의 증가로 인해 계통연계 인버터의 사용이 꾸준하게 증가해 왔다. 계통연계 인버터의 제어를 위해 많이 사용되는 PI 제어기는 구조가 간단하여 제어기 구성이 쉽다는 장점이 있지만 계통 전압에 예상치 못한 전압 외란이 발생할 경우 전류 품질이 떨어지는 단점을 가지고 있다. 이를 극복하기 위해 본 논문에서는 LCL 필터를 사용하는 계통연계 인버터의 상태공간 모델을 이용하여 공진제어기와 적분제어기가 결합된 전 상태궤환 제어기법을 제시한다. 또한 계통외란과 주파수 변동으로 인해 발생하는 주파수 검출성능 향상을 위해 SOGI-PLL을 사용하여 시스템의 안정성을 보장한다. 제안된 기법의 타당성과 성능이 PSIM 시뮬레이션을 통하여 입증된다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.635-641
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• 2016

In many industrial applications that use the electric motors robust controllers are needed. The method using a neural network in order to design a robust controller when a disturbance occurs is studied. Backpropagation algorithm, which is used in a conventional neural network controller is used in many areas, but when the number of neurons in the input layer, hidden layer and output layer of the neural network increases the processing speed of the learning process is slow. In this paper an adaptive PI(Proportional and Integral) controller based on CTRNN(Continuous Time Recurrent Neural Network) for permanent magnet synchronous motors is presented. By varying the load and the speed the validity of the proposed method is verified through simulation and experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.3
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• pp.166-172
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• 1989

The model reference adaptive control algorithm (MRAC), which is one of the methods for controlling the speed of a permanent magnet synchronous motor (PMSM), has been developed using the autoregressive (ARMAX) method. Applying this algorithm to a microprocessor which is used in driving PMSM with PI controller, it has been proved that the response speed of the reference input follows closely that of the reference model. It has also been proved by experiments that the quick speed response without over-shoot could be obtained for the motor system with variable parameters.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.697-702
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• 2004

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation, is studied from an input-output feedback linearization with adaptive algorithm. is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Simulation results are provided for illustration.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.261-264
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• 1993

This paper proposes an adaptive generalized predictive control with feedforward algorithm for steam generator level control in nuclear power plant. The proposed algorithm is shown that the parameters of N-step ahead predictors can be obtained using the parameters of one-step ahead predictor which is derived from plant model with feedforward. Using this property the proposed scheme is an adaptive algorithm which consists of GPC method and the recursive least squares algorithm for identifying the parameters of one-step ahead predictor. Also, computer simulations are performed to evaluate the performance of proposed algorithm using a mathematical model of PWR steam generator Simulation results show good performances for load variation. And the proposed algorithm shows better responses than PI controller does.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.332-345
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• 2013

In this paper, recently, it is described to the piezoelectric transformer technology develops, because it was have to favorable characteristics such as electromagnetic-noise free, compact size, higher efficiency, and superior power density, flux linkage, noiseless, etc. its resonance frequency was used to output waveform of a sine wave. A rotor speed identification method of induction motor based on the theory of flux model reference adaptive system(FMRAS). The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the model are introduced to perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM techniuqe and DC-DC converter. High speed calculation and processing for vector control is carried out by digital signal one chip microprocessor. Validity of the proposed control method is verified through simulation and experimental results.