• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1076-1079
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• 1993

A fuzzy digital controller is combined an autopilot system for compensating the cross coupling effect of the induced roll due to the dynamic characteristic of three fin torpedo. However the utilization of fuzzy chip has many interfacing problems with typical microprocessors of the guidance and control unit. Since a fuzzy digital controller on a microprocessor uses a finite word length A/D converters arul D/A converters, ADC and DAC may generate nonlinear effects such as deadband and limit cycle phenomena. In this paper, the robustness of fuzzy digital controller is tested with ADC a finite word length.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1073-1076
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• 1991

This paper presents a robust model reference adaptive controller for continuous-time single-input single-output linear time-invariant systems which are subjected to output-dependent disturbances as well as bounded external disturbances. In the derived controller form, an additional output error feedback term is included to over-ride the destabilizing effects by the output-dependent disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.56-60
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• 1992

This paper addresses the problem of designing a neural network based controller for a discrete-time nonlinear dynamical system. Using two multi-layered neural networks we first design an indirect controller the weights of which are updated by the informations obtained from system identification. The weight update is executed by parameter optimization method under Lagrangian formulation. For the nonlinear dynamical system, we define several cost functions and by computer simulations analyze the control performances of them and the effects of penalty-weighting values.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.452-456
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• 2004

A study on gust loads alleviation using aircraft control surface was performed. Aeroservoelastic model including control surface controller was formulated and validated by comparing the results of continuous turbulence response analysis with those of MSC/NASTRAN. Optimal control with output feedback was adopted for designing the control surface controller, and the effects of gust loads alleviation was validated by performing the numerical simulation for the controller designed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.51-56
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• 1998

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy logic controller(FLC). The quantitative relation between input and output variables of FLC is obtained by using a qualsi-linear fuzzy model, and an approximate transfer function of FLC is dervied from the comparison of it with the conventional PID controller. Then we analyze in detail the effects of scaling factor using this approximate transfer function and root locus method. Also we suggest an on-line tuning method for scaling factors which employs an sample performance function and a variable reference for tuning index.

• 한국정밀공학회지
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• 제12권7호
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• pp.114-122
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• 1995

A digital preview controller is designed for tandem cold mills to achieve a more improvement of the thickness accuracy. Simultaneously a blocked noninteracting controller is synthesized for rejecting the interactive effects among adjacent stands and for controlling independently each roll stand of tandem cold mills. The performance effects and characteristics of the suggested roll contol system are discussed in the practical viewpoint. The simulaltion results show that the thickness accuracy of tandem cold mills can be largely improved by the blocked noninteracting and digital preview controller.

• 전자공학회논문지SC
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• 제40권6호
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• pp.1-7
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• 2003

본 논문은 비선형 시스템에서 시스템의 출력이 주기적인 특징을 가지는 궤적을 따라가도록 하는 슬라이딩 모드 반복 제어기를 소개한다. 본 논문에서 제안하는 제어기는 전체 시스템을 안정화시키며 출력오차를 어떤 범위 안으로 지수적으로 수렴시키는 슬라이딩 모드 제어기와 추적 오차의 수렴을 위해서 사용되는 반복 제어기로 구성되어 있다. 본 논문에서는 제안하는 슬라이딩 모드 제어기는 기존의 방법과는 다르게 제어입력의 크기가 추적오차의 크기에 비례하게 되어 있어서 시스템의 차수를 올리지 않고 정상상태에서의 채터링(chattering) 문제를 크게 개선하는 특징을 가지고 있다.

• 전기학회논문지
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• 제58권1호
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• pp.187-192
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• 2009

This paper presents a method for designing a robust controller that alleviates disturbance effects and compensates performance degradation owing to the time-delay. Disturbance observer(DOB) approach as a tool of robust control has been widely employed in industry. However, since the Pade approximation of time-delay makes the plant non-minimum phase, the classical DOB cannot be applied directly to the system with time-delay. By using a new DOB structure for non-minimum phase systems together with the Smith Predictor, we propose a new controller for reducing the both effects of disturbance and time-delay. Moreover, the closed-loop system can be made robust against uncertain time-delay with the help of a Pill controller tuning method that is based on a second-order plus dead time modeling technique.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.46-48
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• 1996

In almost all the servo systems, especially for the robot manipulators and numerical control systems, there are resonance effects and nonlinear frictions which should be considered in designing servo controllers. In this paper to compensate friction and track the step-input without steady-state error, the original system is augmented with an integrator and employes $\mu$-Controller design method $\mu$-Controller design method enables to meet not only performance requirements but robust stabilities simultaneously. And there may exist a limit cycles due to interaction between integrator and nonlinear friction. With describing function method, the possibility of limit cycle is checked.

• 제어로봇시스템학회논문지
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• 제11권6호
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• pp.524-529
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• 2005

In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.