• 전기학회논문지
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• 제64권1호
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• pp.90-98
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• 2015

In this paper, an advanced teaching-learning based optimization(TLBO) method for the magnetic levitation controller of Maglev transportation system is proposed to optimize the control performances. An attraction-type levitation system is intrinsically unstable and requires a delicate control. It is difficult to completely satisfy the desired performance through the methods using conventional methods and intelligent optimizations. In the paper, we use TLBO and clonal selection algorithm to choose the optimal control parameters for the magnetic levitation controller. To verify the proposed algorithm, we compare control performances of the proposed method with the genetic algorithm and the particle swarm optimization. The simulation results show that the proposed method is more effective than conventional methods.

• 전기학회논문지
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• 제66권4호
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• pp.701-708
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• 2017

This paper proposes an optimum design method using Teaching-Learning-based optimization for the fuzzy PID controller of Magnetic levitation rail-guided vehicle. Since an attraction-type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the conventional control methods. In the paper, a fuzzy PID controller with fixed parameters is applied and then the optimum parameters of fuzzy PID controller are selected by Teaching-Learning optimization. For the fitness function of Teaching-Learning optimization, the performance index of PID controller is used. To verify the performances of the proposed method, we use a Maglev model and compare the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.

• 전기학회논문지
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• 제57권9호
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• pp.1624-1627
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• 2008

This paper deals with a linear matrix inequality (LMI) approach to the design of a PID controller for an attraction type magnetic levitation system. First, we convert the $H_ {\infty}$ PID controller problem into a static output feedback problem. We then solve the static output problem by using the recently developed penalty function method. Numerical experiments show the effectiveness of the proposed algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1997년도 추계학술대회논문집; 한국과학기술회관; 6 Nov. 1997
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• pp.426-431
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• 1997

In this paper, a sensorless realization method is proposed for the magnetic levitation system. Also we design the robust servo controller which based on the two degree-of-freedom-control theory and H$\sub$.inf./ control theory for the system. From time responses, we confirm that the proposed sensorless method can be applied the magnetic levitation system. Also the designed controller has the good disturbance rejection and the reference tracking performance.

• 한국지능시스템학회논문지
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• 제27권2호
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• pp.106-112
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• 2017

본 논문에서는 자기부상 물류이송시스템의 부상 및 추진제어기 설계 방법을 제안하였다. 부상제어기는 롤과 피치 움직임을 최소화시키기 위해 전자석간의 상호영향을 고려하여 설계하였다. 자기부상이송시스템의 구조적인 단점을 해결하기 위하여 기준입력단에 지수형 필터를 적용하여 기존 제어기의 문제점을 개선하였다. DSP기반의 제어하드웨어를 개발하고, 정격 공극 부상 실험을 통해 부상제어기법이 설계 목표를 만족함을 검증하였다. 추진제어기는 공간벡터 전압변조기법을 사용하고, 레일의 전 구간에 부착된 바코드 정보로부터 절대위치를 감지하여 위치 및 속도 프로파일을 추종하도록 설계하였다. 추진제어 왕복 이동 실험을 통해 위치 제어 결과가 만족할만한 성능임을 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권6호
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• pp.342-350
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• 2003

In this paper, a levitation controller for a magnetic levitation(MagLev) system is designed and implemented. The target to be controlled is PEM(permanent and electromagnet) type with 4-corners levitation which is open-loop unstable, highly non-linear and time-varying system. The digital control system consists of a VME-based CPU board, AD board, PU board, 4-Quadrant chopper, and gap sensor, accelerometer as feedback sensors. In order to estimate the velocity of the magnet, we used 2nd-order state observer with acceleration and gap signal as input and output, respectively. Using the estimated states, a state feedback control law for the plant is designed and the feedback gains are selected by using the pole-placement method. The designed controller is experimentally validated by step-type gap reference change and force disturbance test.

• Journal of Mechanical Science and Technology
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• 제16권12호
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• pp.1643-1651
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• 2002

Magnetic levitation systems are required to have a large operating range in many applications. As one method to solve this problem, Time Delay Control (TDC) is applied to a single-axis magnetic levitation system in this paper A reduced-order observer is utilized to estimate states excluding measurable states in the control law. The system consists of a square air-core solenoid and a circular permanent magnet attached on a plastic ball. Theoretical magnetic forces of the system are obtained on the basis of the location of the magnet around the solenoid. The magnetic levitation force is obtained by the experiment, and then compared with the theoretical one. As the results of the control experiments, the nonlinear controller (TDC : 1-2 ㎜) has a larger operating range than the linear controller (PD control : 1-1.4 ㎜), and is superior to linear. control in the robustness to the modeling uncertainty and the performance of the disturbance rejection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.699-703
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• 1991

A magnetic levitation system with hybrid magnets, which is composed of permanent magnets and electromagnets, consumes less power than the conventional attraction type system. In this paper, we propose PID controller and PID-Fuzzy controller for hybrid magnet. We first present "constant gap" control technology with PID controller. Secondly, "zero power" control technology with PID-Fuzzy hybrid controller is presented.roller is presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1557-1560
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• 1997

In this paper, we have built an experimental magnetic levitation system for a possible use of control education. We have give a mathermatical model of the nonlinear system and have shown the stability region of the linearized system when it is controlled by a PD controller. We also proposed a neural network control system which uses a neural network as a feedforward controller thgether with a conventional feedback PF controller. We have generated a desired output trajectory, which was designed for the benefit of the generalization of the neural network controller, and trained the desired output trajectory, which was desigend for the benefit of the generalization of the neural netowrk controller, and trained a neural network controller with the data of the actual input and the output of the system obtained by applying the desired output trajectroy. A good tracking performance was observed for both the desired trajectiories used and not used for the neural network training.

• 한국인터넷방송통신학회논문지
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• 제19권1호
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• pp.225-229
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• 2019

자기베어링은 기계적인 마찰이 없고 안정적인 동역학 특성을 갖기 때문에 진공 및 청정 환경이나 고정도가 요구되는 분야에서 많이 활용되고 있다. 그러나 자기베어링은 다양한 장점에도 불구하고 일반적으로 제어기가 복잡해서 적용 범위의 확산이 제한적이다. 본 논문에서는 복잡도가 낮은 디지털 방식의 자기베어링 제어기를 제안하였다. 또한 디지털 제어기 성능열화의 주된 원인인 아날로그 신호를 디지털 신호로 변환하는 과정에서 발생하는 오류와 제어 알고리즘 구현상의 문제점들을 분석하고 해결하였다. 제안한 제어기를 실제 자기베어링에 적용한 실험을 통해 제어기가 자기부상 목표 정밀도를 갖는 것을 확인하였다.