• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.674-679
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• 2000

This research is concerned with the modeling technique and active vibration controller design for slewing smart structures. When cantilever beam rotates about axes perpendicular to the undeformed beam's longitudinal axis, it experiences inertial loading. Hence, the beam vibrates from the initial stage of slewing, In this paper, the analytical model for a single slewing flexible beam with surface bonded piezoelectric sensor and actuator is developed using the Hamilton's principle with discretization by the assumed mode method. It is found from experiments that the theoretical model lacks the frictional effect. The frictional effect is incorporated into the equations of motion by employing the coupling factor. Theoretical and experimental results show problems arising in modeling and controller design.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.281-286
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• 2000

This paper describes a lateral guidance system of an unmanned vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in the unmanned vehicle simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the learning pattern, learning itself, and the adequacy of the design controller. A computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. Good results were obtained. Also, the real unmanned electrical vehicle using neural network controller verified good results.

• 전력전자학회논문지
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• 제17권1호
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• pp.67-76
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• 2012

This paper proposes the aggregated modeling and control of integated boost-flyback converter (IBFC) for understanding of dynamics characteristic and designing of relevant controller. The basic concept of the aggregated modeling is to substitute the boost or the flyback converter with an equivalent current source. Since each converter with equivalent current source corresponds to the basic boost and flyback converters, the overall mathematical process is significantly simplified for the modeling. Afterwards each result is combined to construct the complete model of the IBFC, and the relevant controller is designed through the achieved small-signal model. Simulation and experimental results show excellent agreement with the theoretical expectations.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• Journal of Astronomy and Space Sciences
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• 제14권2호
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• pp.386-394
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• 1997

본 연구에서는 유연모드를 고려한 위성체 모델링 방법들을 소개하고, 이에 따라 3축 안정화 위성의 유연모드를 모델링하였다. 이 모델을 강체에 대해 설계되었던 반작용휠을 이용한 자세제어루프에 적용하였다. 본 연구에서는 유한요소모델이 완성되기 전 단계에서 집합모드모델 중 전역모드모델을 이용하는 것을 제안하였고, 이를 유한요소법을 이용하여 계산된 모델과 제어기 필터 설계의 관점에서 비교하였다. 새로운 유연모드가 적용됨에 따라 제어기 요구조건을 만족시키기 위한 필터가 필요하여 반작용휠의 모터제어기 루프와 축제어기 루프에 각각 1차 필터를 설계하여 추가하였다. 제어루프 설계 및 시뮬레이션을 위해 MATLAB/Simulink를 사용하였다.

• 전기전자학회논문지
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• 제21권4호
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• pp.424-427
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• 2017

원점이나 원점 근방에 있는 극을 포함하고 있는 시간지연시스템에 대하여 스미스 예측제어기를 적용할 경우 외란에 의한 정상상태 오차가 발생한다. 또한 모델링 오차가 존재할 경우에도 외란에 의한 오차 발생으로 인하여 제어기 구성이 어렵게 된다. 이에, 본 논문에서는 이러한 시스템들에 대한 외란의 영향을 제거하기 위한 새로운 제어기를 구성하였다. 외란을 측정할 수 있는 외란관측자를 제안하였으며, 관측된 외란을 이용하여 외란의 효과를 소거할 수 있는 제어기를 구성하였다. 그 결과, 외란 및 모델링 오차의 영향을 제거할 수 있는 새로운 제어기를 설계할 수 있었다. 구성된 제어기를 발전소 과열기 및 증기압 제어에 적용하여 제안한 시스템의 효용성을 입증하였다.

• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1466-1474
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• 2003

This paper presents a system modeling, controller design and implementation for a rotational inverted pendulum system (RIPS), which is an under-actuated system and has the problem of unattainable velocity state. Two control strategies are applied to the RIPS. One is a sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback. The other is the disturbance observer which estimates disturbance and some modeling errors of RIPS with less computational effort. Some simulations and various kinds of experiments are performed in order to verify that the proposed controller has the ability to control RIPS whose velocity is assumed to be unavailable. The results of the simulations and experiments show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions as well as the robustness to model uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.779-782
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• 1996

Repetitive control is a proposed control strategy in view of the internal model principle and achieves a high accuracy asymptotic tracking property by implementing a model that generates the periodic signals of period into the closed-loop system. Since the repetitive control system contains a periodic signal generator with positive feedback loop, which reduces the stability margin, in the overall closed-loop system, the stability of the closed-loop system should be considered as an important problem. In case that a real system has plant uncertainties which are not represented through modeling, the robust stability problem of the repetitive control system has not been considered sufficiently. In this paper, we propose the robust stability condition for the system with modeling uncertainty. The proposed robust stability condition will be obtained using the robust performance condition in the H$_{\infty}$ control. Moreover, by use of the proposed robust stability condition, we propose a procedure that designs a repetitive controller and a feedback controller simultaneously which can stabilize the overall closed-loop system robustly and which can also do the closedloop system without repetitive controller..

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.502-506
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• 1992

In this study, we proposed the fuzzy modeling method and designed a model-based logic controller for Activated and Sludge Process(A.S.P.) in sewage treatment. The identification of the structure of fuzzy implications is carreid out by use of fuzzy c-means clustering algorithm. And to identify the parameters of fuzzy implications, we used the complex and the least square method. To tune the premise parameters automatically the complex method is implemented. The model-based fuzzy controller is designed by rules generated from the identified A.S.P. fuzzy model. The feasibility of the proposed approach is evaluated through the identification of the fuzzy model to describe an input-output relation of the A.S.P.. The performance of identified model-based fuzzy controller is evaluated through the computer simulations.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 특별세미나 특별세션
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• pp.145-159
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• 2006

This paper describes the development of a clustering based fuzzy controller of an electromagnetic suspension vehicle using gain scheduling method and Kalman filter for a simplified single magnet system. Electromagnetic suspension vehicle systems are highly nonlinear and essentially unstable systems For achieving the levitation control of the DC electromagnetic suspension system, we considered a fuzzy system modeling method based on clustering algorithm which a set of input/output data is collected from the well defined Linear Quadratic Gaussian(LQG) controller. Simulation results show that the proposed clustering based fuzzy controller methodology robustly yields uniform performance with adequate gap response over the mass variation range.