• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.771-782
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• 1991

In industrial multivariable plants, it is ofte the case that the plant outputs are measured in similar components not simultaneously but serially. In this paper, the problem of estimating the state vector of the plant based on the data obtained from such a measuring scheme is considered, and a special type of observer(referred to as a $'$multiple serial-sampling$'$ type observer) which renews its internal states whenever a new group of data is obtained is proposed. It is proved that such an observer can be constructed for almost every sampling period if the palnt is observable as a continuous-time multivariable system, and that the poles of the closed-loop system using the multiple serial-sampling type observer consist of the poles of the observer and those of the state feedback system. The behaviors of the observer and the closed-loop system are studied by simulation. The results of simulation indicate that a multiple serial-ampling type observer can estimate the state of the plant more accurately than the ordinary type observers and improve the closed-loop performance, especially, in the existence of measuring noise.ng noise.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.853-858
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• 2007

In this paper, a seesaw system composed with a moving cart on the rail and seesaw frame is made to demonstrate the effectiveness of the control theory. The control aim is to maintain an equilibrium of seesaw frame in spite of various initial conditions and an allowable disturbance. To solve this control problem, a PI-type state feedback controller using reduced-order observer is implemented and applied to the seesaw system. The reduced-order observer can be used to estimate the state variables in the case of the limit of sensor number or the constraint on setting sensors and the cost. A series of simulation are carried out to verify the effectiveness of the control system.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1682-1683
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• 2007

본 논문은 시변 파라미터를 갖는 직류 모터의 적응 제어를 위한 온라인 상태궤환 제어시스템을 구성한다. 모터의 전기자 저항은 공칭값에 대하여 가우시안 랜덤변수로 가정하고 온라인 최소자승 추정법을 이용하여 실시간으로 추정한다. 모터의 부하 토크 또한 시변 특성을 가지며 이런 시스템 환경의 변화에 대해서도 설정치를 잘 추종하는 특성을 갖도록 한다. 컴퓨터 시뮬레이션을 통해 제어기법의 타당성을 검증하며 기존의 상태궤환 제어기법과 비교분석하여 성능의 우수성을 입증한다.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.6
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• pp.37-46
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• 2001

In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to around excitation modeled by partially stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function, constraint functions and their gradients are computed by the parameterization of control gain with Riccati matrix. Full state feedback controllers designed by proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed for the production of actuator. LQG controllers composed of Kalman filter and LQR designed by proposed method perform well with little deterioration. So it is possible to design output feedback controllers satisfying constraints on various maximum responses of structures.

• Journal of KIISE
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• v.42 no.6
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• pp.748-754
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• 2015

This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.380-388
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• 2016

Using the magnet gear, it is possible to transmit power without mechanical contact. As the drive shaft in a magnet gear-based speed reducer system is isolated from the drive shaft, the system is a two-inertia resonance system that should cope with an external load with the limited air-gap stiffness. On the other hand, the drive shaft or low-speed side is controlled only by the torque of the drive shaft through an air-gap, and the excessive oscillation or the slip can then be generated because of an abrupt disturbance that is different from the general mechanical gear system. Therefore, the disturbance loaded at the low speed side should be measured or estimated, and considered in the control of the driving shaft. This paper proposes a novel full-state feedback controller with a reduced-order observer for the speed reducer system using a magnet gear with a unified harmonic modulator. The control method was verified by simulation and experiment. To estimate the load at the low speed side, a novel observer was designed, in which the new state variable is introduced and the new state equation is formulated. Using a full-state feedback controller including the observer, the test result against disturbance was compared with two D.O.F PI speed controllers. The pole slip was compensated within relatively a short time, and the simulation result about the estimated variable shows a similar tendency to the test result. The test results showed that the magnet gear-based reducer can be applied to an accurate servo system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.5
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• pp.1587-1600
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• 1991

본 연구에서는 로봇조작기를 강체부와 유연한 외팔보로 이루어진 모델로 설정 한 후 확장된 Hamilton의 원리를 적용하여 제어계의 운동방정식을 유도하였다. 계를 유한개의 제어 모드와 잔류 모드로 구분하고, 제어 모드에 대해 최적제어를 수행하기 위해 관측기를 설계하였으며, 진동에 관련된 측정 불가능한 상태변수를 추정하였다. 분석과 검토는 서보모터가 모든 제어를 담당하는 방식과 서보모터의 제어 방식에 작동 기를 추가시켜 병행 제어하는 다입출력 방식으로 구별하여 수행하였다.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.338-339
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• 2018

최근 분산전원 시스템 개발로 인해 계통연계 인버터의 사용이 증가해 왔다. 계통연계 인버터의 주요한 역할은 계통연계 환경에서의 안정적인 운전과 계통 사고 시 중요 부하에 대한 연속적인 전력을 공급하기 위한 독립운전에 있다. 각 모드 전환시의 출력전압의 변동성과 과도응답 특성을 개선하기 위해 최근 다중 루프 및 간접 전류 제어 방식이 계통연계 인버터에 적용되었다. 하지만 이러한 제어 방식은 캐패시터 전압 및 인버터 전류의 측정이 요구되어 시스템의 비용 및 복잡성을 증가시키게 된다. 본 논문에서는 이산시간 상태공간에서의 전상태 관측기를 설계하여 무순단 절체 동작 시 제어기가 요구하는 변수를 추정하고 이를 궤환신호로 사용하여 시스템의 설계 비용 및 복잡성을 줄인다. 또한 계통연계 시 계통유입 고조파 전류를 억제하기 위해 일반적으로 사용되는 기존 공진형 제어기의 과도 응답을 개선하기 위해 이산시간에서 슬라이딩 모드와 공진제어기가 결합된 새로운 제어기 구조를 제안한다. 제안된 기법의 타당성은 PSIM 시뮬레이션을 통하여 입증된다.

• Composites Research
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• v.28 no.6
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• pp.383-388
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• 2015

Ionic Polymer-Metal Composite (IPMC) consisting of soft membrane plated by platinum electrode layers on both surfaces generates electric energy when subjected to various mechanical stimuli. The paper proposes a circuit model that describes the physical composition of IPMC to predict the voltage generation characteristic corresponding to bending motion. The parameter values in the model are identified to minimize the RMS error between the real and simulated outputs. Following the design of IPMC circuit model, the state observer of the model is designed by using pole placement technique which improves the model accuracy. State observer design technique is also applied to find the inverse model which estimates the input bending angles from the output voltage data. The results show that the inverse model estimates input bending angles fairly well enough for the further applications of IPMC not only as an energy harvester but also as a bending sensor.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.365-369
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• 2012

We propose a vision-based method that estimates train position and movement for railway monitoring in which we use a fuzzy classifier to determine train states. The proposed method employs frame difference and background subtraction for estimating train motion and presence, respectively. These features are used as the linguistic variables of the fuzzy classifier. Experimental results show that the proposed method can correctly estimate train position and movement. Therefore the method can be used for railway monitoring systems which estimate crowd density or protect safety.