• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.1
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• pp.73-80
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• 2001

구조물이 가지는 에너지의 확률밀도함수를 이용한 능도제어 알고리듬을 제안한다. 구조물의 에너지는 Rayleigh 확률분포를 가지는 것으로 가정된다. 이것은 에너지가 항상 양의 값을 가지고 최소에너지가 발생할 확률은 1이라는 조건을 Rayleigh 확률분포가 만족시킨다는 사실에 근거한다. 제어력의 크기는 가정된 확률밀도함수에 따라 구조물의 에너지가 설계자에 의해 설정된 에너지 임계값을 넘을 확률의 크기에 비례하도록 산정되며, 제어력의 방향은 Lyapunov 제어기 설계기법에 따라 결정된다. 제시된 알고리듬은 LQR 제어기와 비교하여 최대응답을 줄이는 효과를 가지며, 제어력의 임계를 고려할 수 있는 장점을 가진다. 또한 Lyapunov 제어기에서 발생가능한 채터링(chattering)현상을 피할 수 있다.

• Proceedings of the KAIS Fall Conference
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• 2001.05a
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• pp.119-123
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• 2001

본 논문에서는 자동화 사격장 Pop-Up시스템의 안정성 및 성능 향상을 위해 예측제어기를 설계하여 시간지연에 따른 문제를 보상하였다. 확률 모델에 기반한 예측제어기는 지연된 이전의 값들로부터 선형예측 기법과 확률함수를 이용하여 실제의 값을 추정하며, 이를 제어기에 적용하여 시간지연에 따른 문제점을 최소화하였다. 제안된 알고리즘의 타당성을 검정하기 위해 사격용 Pop-Up시스템에 본 알고리즘을 실현하였으며, 상이한 시간지연과 이득 변화에 따른 제어기의 성능을 관측하였다. 실험결과 제안된 예측제어기는 시간지연에 대해 PID 제어기보다 빠른 수렴 특성을 보이며, 제어기의 안정범위 내에서 허용할 수 있는 최대 시간지연 값도 증가시킬 수 있었다. 따라서 사격용 타겟의 Pop & Up동작이 제어시간 이내에 원활하게 작동되어 연속 사격의 실시간 제어를 효율적으로 수행하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1292-1297
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• 2000

For dynamic system under the external irregular disturbance, a performance of the controller designed by using of the 'Heo-stochastic control methodology' is investigated by simulations and experiments. MIMO Flexible cantilever beam, sticked with piezoceramics used as a sensor and actuator, under the irregular disturbance at bottom is modelled in physical domain. Dynamic moment equation about the system is derived through both the Ito's stochastic differential equation and Fokker-Planck-Kolmogoroff equation and also system's characteristics in stochastic domain is analyzed. In this study, the controller suppresses the amplitude of the system's moment response to the external disturbance. MIMO PI controller('Heo-stochastic MIMO PI controller') is designed in the stochastic domain and the response characteristics are investigated in the time domain

• 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 the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.464-469
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• 2009

This paper discusses a robust observer-based output-feedback stabilization of an uncertain Takagi-Sugeno (T-S) fuzzy system in a network. In the networked control system, the input delay occurs inevitably and it is expressed by the Markovian stochastic process. To design robust sampled-data observer-based output-feedback controller, we discretize the T-S fuzzy system and represent as a jump system. Stochastic robust stabilization condition is formulated in terms of linear matrix inequalities.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.9-17
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• 2021

In this paper, we present a simple and fast supervised learning framework based on model predictive control so as to learn motion controllers for a physic-based character to track given example motions. The proposed framework is composed of two components: training data generation and offline learning. Given an example motion, the former component stochastically controls the character motion with an optimal controller while repeatedly updating the controller for tracking the example motion through model predictive control over a time window from the current state of the character to a near future state. The repeated update of the optimal controller and the stochastic control make it possible to effectively explore various states that the character may have while mimicking the example motion and collect useful training data for supervised learning. Once all the training data is generated, the latter component normalizes the data to remove the disparity for magnitude and units inherent in the data and trains an artificial neural network with a simple architecture for a controller. The experimental results for walking and running motions demonstrate how effectively and fast the proposed framework produces physics-based motion controllers.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.293-299
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• 2003

This paper discusses a design of intelligent controller with time delay for Internet-based remote control. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The Takagi-Sugeno (T-S) fuzzy system with uncertain input delay is utilized to represent nonlinear plant. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The robust stochastic stabilizibility of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). An experimental results is provided to visualize the feasibility of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.525-528
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• 2005

Much of the study has been dong on the design of dual controller that guarantee the stability and improvement of the system performance. A dual controller concept is proposed to consist of first controller estimates the control law and second controller suppresses the combined noises due to numerical error and internal noise as well. These irregular disturbances are not only increasing the fatigue but also destabilize the system because of unwanted output performance. The 'stochastic controller' is used to suppress the irregular random disturbance. Simulation is conducted to reveal that the proposed dual stochastic controller is highly efficient one to control a system hybrid noises.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.757-763
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• 2005

Much of the study has been done on the design of dual controller that guarantee the stability and improvement of the system performance. A dual controller concept is proposed to consist of first controller estimates the control law and second controller suppresses the combined noises due to numerical error and internal noise as well. These Irregular disturbances are not only increasing the fatigue but also destabilize the system because of unwanted output Performance. The 'stochastic controller' is used to suppress the irregular random disturbance. Simulation is conducted to reveal that the proposed dual stochastic controller is highly efficient one to control a system hybrid noises.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.537-540
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• 1987

항공기가 평형상태로 비행하는 도중 돌풍과 같은 외부교란을 만난 교란상태운동은 선형화된 미분방정식으로 표현되며 비교적 짧은 비행시간동안의 비행은 선형시 불변계가 된다. 돌풍은 Gauss-Markov확률과정으로 모델링 되며, 항공기가 돌풍을 만난 교란상태운동은 시스템론적으로 보면 백색잡음이 성형필터를 거쳐 계에 입력되는 것과 같다. 초기의 설계방법은 고전적인 주파수영역에서의 해석방법을 사용하였으나 1960년대에 최적제어이론이 도입되면서 평가함수를 사용하여 원하는 비행특성을 얻는 방법을 사용하게 되었다. 그 후 계에 입력되는 외란과 측정시의 잡음으로 인한 불확실한 측정량으로부터 최적상태변수의 추정을 위해 필터링이론을 도입한 확률제어이론을 적용하여 자동조종장치를 설계하게 되었다. 이때까지는 연속제어계로 설계되었으며 그 후 측정신호를 샘플링하여 연속제어계와 등가의 이산제어계를 사용한 자동조종장치가 등장하였으며 이 경우 설계기법으로는 연속제어계를 사용하고 실현시킬 때는 디지털컴퓨터를 사용하였다. 이는 제어하는 동안 계의 계수와 제어법칙을 바꾸어 줄 수 있는 이산제어계의 장점을 이용하지 못하므로 처음부터 계를 등가의 이산계로 보고 제어계를 설계하는 방법이 도입되었다. 이 때 샘플링간격의 결정과 Quantization 영향이 설계시 고려되어야 한다.