• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.182-183
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• 2004

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1147-1148
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.188-191
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• 1996

In this paper, we derive dynamic equation of double pole inverted pendulum using Lagrangian equation, and design the fuzzy sliding mode controller. We demonstrate that the designed controller regulates double pole simultaneously regardless of cart position by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.45.1-45
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• 2002

$\textbullet$ Introduction $\textbullet$ Takagi-Sugeno Fuzzy Model and Sliding Mode Controller $\textbullet$ Observer and Controller Design $\textbullet$ Simulations $\textbullet$ References

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.1-11
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• 2004

◎Origin ·Mark Weiser(52-99)：Xerox PARC CTO ·Ubique in Latin = Everywhere ◎Simila Terms ·Ubiquitous Network/IT ·Pervasive/Nomadic/Wearable/Disappearing Computing ◎ Characteristics ·Everywhere, Mobility ·w/o Awareness w/ Awareness tech： e.g., Speedpass of Mobil, Intelligent cart of Wal-Mart(omitted)

• Journal of Drive and Control
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• v.13 no.4
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• pp.23-30
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• 2016

This paper presents a control-oriented dynamical model of a towing rope system with variable-length. In this system, a winch driven by a motor's torque uses the towing rope to pull a cart. In general, it is a difficult and complicated process to obtain an accurate mathematical model for this system. In particular, if the rope length is varied by operating the winch, the varying rope dynamics needs to be considered, and the key physical parameters need to be re-identified... However, real time parameter identification requires long computation time for the control scheme, and hence undesirable control performance. Therefore, in this article, the rope is modeled as a straight massless segment, with the mass of rope being considered partly with that of the cart, and partly as halfway to the winch. In addition, the changing spring constant and damping constant of the towing rope are accounted for as part of the dynamics of the winch. Finally, a reduced-order observer-based servomechanism controller is designed for the system, and the performance is evaluated by computer simulation.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.1-7
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• 2009

This paper presents a sliding mode controller based on Ackermann's formula and applies it to stabilizing a two-wheeled mobile inverted pendulum in equilibrium. The mobile inverted pendulum is a system with an inverted pendulum on a mobile cart. The dynamic modeling of the mobile inverted pendulum was established under the assumptions of a cart with no slip and a pendulum with only planar motion. The proposed sliding mode controller was based upon a class of nonlinear systems whose nonlinear part of the modeling can be linearly parameterized. The sliding surface was obtained in an explicit form using Ackermann's formula, and then a control law was designed from reachability conditions and made the sliding surface attractive to the equilibrium state of the mobile inverted pendulum. The proposed controller was implemented in a Microchip PIC16F877 micro-controller. The developed overall control system is described. The simulation and experimental results are presented to show the effectiveness of the modeling and controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.886-890
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• 2007

Machine fault prognosis techniques have been considered profoundly in the recent time due to their profit for reducing unexpected faults or unscheduled maintenance. With those techniques, the working conditions of components, the trending of fault propagation, and the time-to-failure are forecasted precisely before they reach the failure thresholds. In this work, we propose an approach of Least Square Regression Tree (LSRT), which is an extension of the Classification and Regression Tree (CART), in association with one-step-ahead prediction of time-series forecasting technique to predict the future conditions of machines. In this technique, the number of available observations is firstly determined by using Cao's method and LSRT is employed as prognosis system in the next step. The proposed approach is evaluated by real data of low methane compressor. Furthermore, the comparison between the predicted results of CART and LSRT are carried out to prove the accuracy. The predicted results show that LSRT offers a potential for machine condition prognosis.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.323-333
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• 2011

We analyzed using logistic to find factors with a mental disorder because logistic is the most efficient way assess risk factors. In this paper, we applied data mining techniques that are logistic, neural network, c5.0, cart and Bayesian network to delirium data. The Bayesian network method was chosen as the best model. When delirium data were applied to the Bayesian network, we determined the risk factors associated with delirium as well as identified the network between the risk factors.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.291-300
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• 1999

본 논문은 인공신경망과 귀납적 학습방법 등의 인공지능 방법과 선물가격결정에 대한 기존 재무이론을 사용하여 일상어휘로 표현되는 파생상품 가격예측 모형을 개발하는데 있다. 모형의 개발은 1단계로 인공신경망이나 기존의 선물가격결정이론(평균보유비용모형이나 일반균형모형)을 이용하여 선물 가격을 예측한 후, 서로 비교분석하여 인공신경망 모형의 우수성을 확인하였다. 귀납적 학습방법중 CART 알고리듬을 사용하여 If-Then 규칙을 생성하였다. 특히 실용적 측면에서 선물가격의 일상어휘화를 통한 모형개발을 여러 가지 방법으로 시도하였다. 이러한 선물가격 예측모형의 유용성은 일단 If-Then 규칙으로 표현되어 전문가의 판단에 확실한 이론적인 근거를 제시할 수 있는 장점이 있으며, 특히 의사결정지원시스템으로 활용화 될 경우 매우 유용한 근거자료로 활용될 수 있다. 이러한 선물가격 예측모형은 정확성은 분석표본과 검증표본으로 나누어 검증표본에서 세가지 기본모형(평균보유비용모형, 일반균형모형, 인공신경망 모형)과 각 모형의 귀납적 학습방법 모형의 다른 3가지 어휘표현방법 3가지를 모형별로 비교 분석하였다. 분석결과 인공신경망모형은 상당한 예측력을 갖고 있는 것으로 판명되었으며, 특히 CART를 기반으로 한 일상어휘 기반의 선물가격예측 모형은 예측력이 높은 것으로 나타났다.