• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2005년도 춘계학술대회
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• pp.538-541
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• 2005

In tapping mode atomic force microscopy(TM-AFM). the vibro-contact response of a resonating tip is used to measure the nanoscale topology and other properties of a sample surface. However, the nonlinear tip-surface interact ions can affect the tip response and destabilize the tapping mode control. Especially it is difficult to obtain a good scanned image of high adhesion surfaces such as polymers and biomoleculars using conventional tapping mode control. In this study, theoretical and experimental investigations are made on the nonlinear dynamics and control of TM-AFM. To analyze the complex dynamics and control of the tapping tip, the classical contact models are adopted due to the surface adhesion. Also we report the surface adhesion is an additional important parameter to determine the control stability of TM-AFM. In addition, we prove that it is more adequate to use Johnson-Kendall-Roberts (JKR) contact model to obtain a reasonable tapping response in AFM for the soft and high adhesion samples.

• Transactions on Control, Automation and Systems Engineering
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• 제2권3호
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• pp.207-213
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• 2000

This paper introduces a high-performance speed control system based on artificial neural networks(ANN) to estimate unknown parameters of a DC servo motor. The goal of this research is to keep the rotor speed of the DC servo motor to follow an arbitrary selected trajectory. In detail, the aim is to obtain accurate trajectory control of the speed, specially when the motor and load parameters are unknown. By using an artificial neural network, we can acquire unknown nonlinear dynamics of the motor and the load. A trained neural network identifier combined with a reference model can be used to achieve the trajectory control. The performance of the identification and the control algorithm are evaluated through the simulation and experiment of nonlinear dynamics of the motor and the load using a typical DC servo motor model.

• 전기학회논문지
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• 제64권2호
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• pp.289-296
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• 2015

In this paper, we propose the nonlinear control based on singular perturbation theory for position tracking and yaw regulation of planar motor. Singular perturbation theory is characterized by the existence of slow and fast transients in the system dynamics. The proposed method consists of auxiliary control to decouple error dynamics. We develop model reduction with control input. Also, we derIve decoupled error dynamics with auxiliary input. The controller is designed in order to guarantee the desired position and yaw regulation without current feedback or estimation. Simulation results validate the effect of proposed method.

• Structural Engineering and Mechanics
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• 제64권4호
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• pp.495-504
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• 2017

This paper proposes a new direct numerical integration algorithm for solving equation of motion in structural dynamics problems with nonlinear stiffness. The new implicit method's degree of accuracy is higher than that of existing methods due to the higher order of the acceleration. Two parameters are defined, leading to a new family of unconditionally stable methods, which helps to take greater time steps in integration and eliminate concerns about the duration of solving. The method developed can be utilized for a number of solid plane finite elements, examples of which are given to compare the proposed method with existing ones. The results indicate the superiority of the proposed method.

• 전자공학회논문지
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• 제50권7호
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• pp.253-257
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• 2013

본 논문은 지연된 출력과 미지의 외란을 갖는 비선형 시스템에 대한 강인 관측기 설계방법을 제안한다. 지연된 출력의 존재에도 불구하고 관측기의 추정오차에 대한 외란의 효과를 원하는 수준까지 줄일 수 있음을 보인다. 강인 관측기의 존재조건은 시간 지연 값에 의존적인 선형행렬 부등식을 이용하여 제시한다. 마지막으로 제안한 결과의 유효성을 증명하기 위하여 수치 예제를 제공한다.

• 전자공학회논문지SC
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• 제49권3호
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• pp.26-30
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• 2012

본 논문에서는 출력에 시간지연이 존재하는 이산 시간 비선형 시스템에 대한 상태관측기 설계방법을 제안한다. 비선형항에 대한 Lipschitz 조건을 가정하고 비선형항을 하나의 상태변수처럼 고려함으로써 비선형 이산시간 오차동역학방정식의 안정도 문제가 시간지연을 갖는 선형방정식의 안정도 문제로 변환될 수 있음을 보인다. 또한, 시간 지연 값에 의존적인 충분조건을 선형행렬 부등식을 이용하여 제시한다. 마지막으로 제안한 결과의 유효성을 증명하기 위하여 모의실험 예제를 제공한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.173.4-173
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• 2001

This paper presents a stable nonlinear adaptive control for AUV(Autonomous Underwater Vehicle) by using neural network. AUV's dynamics are highly nonlinear, and their hydrodynamic coefficients vary with different operational conditions. In this paper, the nonlinear uncertainties of the AUV's dynamics are approximated by using LPNN(Linearly parameterized Neural Network). The presented controller is consist of three parallel terms; linear feedback control, sliding mode control, and adaptive control(LPNN). Lyapunov theory is used to guarantee the stability of tracking errors and neural network´s weights errors. Numerical simulations for nonlinear control of the AUV show the effectiveness of the proposed techniques.

• 제어로봇시스템학회논문지
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• 제18권1호
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• pp.1-6
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• 2012

In this paper, an adaptive fuzzy control system is proposed for the speed control of the ASV (Autonomous Surface Vehicle) with nonaffine nonlinear system dynamics. We consider the turning speed of the screw propeller to be the control input instead of thrust so that we do not have to know the exact function between turning speed and thrust. But in this case, the ASV becomes a nonaffine nonlinear system because thrust is a nonlinear function of the turning speed. To solve this problem, we propose a Takagi-Sugeno fuzzy-model-based control system and simulation studies are performed. Simulation results show the effectiveness of the proposed control scheme.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1251-1258
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• 2003

This paper presents a nonlinear robust approach to the slip control problem for a torque converter bypass clutch in a passenger car. The proposed nonlinear robust controller builds upon only the measurements avail-able from inexpensive sensors that are already installed in passenger cars for control. The issue of torque estimation problems for the implementation of the proposed controller is addressed. The stability of the internal dynamics is investigated, upon which a nonlinear robust controller is designed using input-output feedback linearization and Lyapunov redesign technique. The performance of the designed controller is validated by simulation studies.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.569-571
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• 1998

In this paper, a new method of conrolling chaotic nonlinear systems is proposed. Firstly, the dynamics of a chaotic nonlinear system is separated into a linear part and a nonlinear part. Secondly, the nonlinear part is approximated using a radial basis function network (RBFN) and canceled from the controlled system. Then, the resulting system has only the linear part added with very weak nonlinearity. Finally, a simple linear state feedback control law is designed for the linear part. In the meanwhile, a theorem justifying this concept is presented and proved. Comparing with the feedback linearization, the proposed method can be applied regardless of the functional form of the controlled dynamics. The proposed method is applied by simulation to the Duffing system and the Lorenz system and satisfactory results are obtained.