• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.256-263
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• 2010

The paper proposes a sensorless speed control strategy for a PMSM (Permanent Magnet Synchronous Motor) based on a new SMO (Sliding Mode Observer), which substitutes a signum function with a sigmoid function. To apply robust sensorless control of PMSM against parameter fluctuations and disturbance, the high speed SMO is proposed, which estimates the rotor position and angular velocity from the back EMF. The low-pass filter and additional position compensation of the rotor are used to reduce the chattering problem commonly found in sliding mode observer with signum function, which becomes possible by applying the sigmoid function with the control of a switching function. Also the proposed sliding mode observer with the sigmoid function has better efficiency than the conventional sliding mode observer since it adjusts the observer gain by variable boundary layer and estimates the stator resistance. The stability of the proposed sliding mode observer is verified by the Lyapunov second method in determining the observer gain. The validity of the proposed high speed PMSM sensorless velocity control has been demonstrated by real experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.589-592
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• 1996

It is well known that robust compensators designed by the block-diagonal Lyapunov function approaches are conservative while they are popular in practice because of their computational easiness. In this note, we develop a systematized version of conventional block-diagonal Lyapunov function approaches by deriving two separated optimizations based on the guaranteed cost control method. The proposed method generates reasonable robust compensators in practice.

• KIEE International Transaction on Systems and Control
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• 제12D권1호
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• pp.43-50
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• 2002

In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.

• 대한전자공학회논문지
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• 제26권1호
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• pp.1-9
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• 1989

적응제어의 수렴분석 방법이 지난 수십년간 연구되어 왔으나, 적응제어 시스템의 고속수렴에 대한 구조적 중요성은 아직도 논쟁이 되고 있다. 본 논문은 적응제어 error 모델에 대한 지수적 수렴속도의 상대적 개선방법을 고찰하였다. Error시스템의 궤환구조를 변화시킴으로써 수렴속도를 개선하기 위해Lyapunov의 직접방식을 적응제어 시스템에 적용하였다. 몇가지 simulation 예를 들어, 이 방법의 고속수렴과 robustness를 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.38.1-38
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• 2001

In this paper, the vibration suppression problem of an axially moving power transmission belt is investigated. The equations of motion of the moving belt is first derived by using Hamilton´s principle for systems with changing mass. The total mechanical energy of the belt system is considered as a Lyapunov function candidate. Using the Lyapunov second method, a nonlinear boundary control law that guarantees the uniform asymptotic stability is derived. The control performance with the proposed control law is simulated. It is shown that a boundary control can still achieve the uniform stabilization for belt systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.260-265
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• 1992

This paper presents an adaptive control scheme for flexible joint robot manipulators. This control scheme is based on the Lyapunov direct method with the arm energy-based Lyapunov function. The proposed adaptive control scheme uses only the position and velocity feedback of link and motor shaft. The adaptive control system of flexible joint robots is asymptotically stable regardless of the joint flexibility value. Therefore, the assumption of weak joint ealsticity is not needed. Also, joint flexibility value is unknown. Simulation results are presented to show the feasibility of the proposed adaptive control scheme.

• 제어로봇시스템학회논문지
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• 제2권3호
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• pp.142-147
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• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural network. The weight-update rule of multilayer neural network is derived to satisfy Lyapunov stability. The whole control system constitutes controller using feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.237-242
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• 2015

This paper presents a method to enhance tracking performance of an input-constrained bilinear system using MPC (Model Predictive Control) when a feasible tracking control is known. Since the error dynamics induced by the known tracking control is asymptotically stable, there exists a Lyapunov function for the stable error dynamics. By defining a cost function including the Lyapunov function and describing tracking performance, an MPC law is derived. In simulation, the performance of the proposed MPC law is demonstrated by applying it to a converter model.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.169-175
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• 2002

A sliding mode control of spacecraft attitude tracking with actuator, especially reaction wheel, is presented. The sliding mode controller is derived based on quaternion parameterization for the kinematic equations of motion. The reaction wheel dynamic equations represented by wheel input voltage are presented. The input voltage to wheel is calculated from the sliding mode controller and reaction wheel dynamics. The global asymptotic stability is shown using a Lyapunov analysis. In addition the robustness analysis is performed for nonlinear system with parameter variations and disturbances. It is shown that the controller ensures control objectives for the spacecraft with reaction wheels.

• 한국정밀공학회지
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• 제14권4호
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• pp.88-96
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• 1997

This paper suggests a new non-linear friction compensation for digital control systems. This control adopts a hysteresis nonlinear element which can introduce the phase lead of the control system to compensate the phase delay comes from the inherent time delay of a digital control. A proper Lyapunov function is selected and the Lyapunov direct method is used to prove the asymptotic stability of the suggested control.