• Korea Trade Review
• /
• v.45 no.5
• /
• pp.117-139
• /
• 2020

In case of international long-term transactions, there are various risks of economic change of circumstances including skyrocketing price increase and shortage of raw material, as well as force majeure in a general sense. Nevertheless, pretty many of international long-term commercial contracts do not include the provisions of renegotiation and adaptation of the contract. In this case, possibility of renegotiation and adaptation depends mainly on the applicable law. Namely, it may be possible or not, according to choice of law. The reason is that national laws have nuances each other, and most of national courts are traditionally reluctant to accept hardship. and also, provisions of international uniform law (CISG) has ambiguity and inflexibility in relation to the problems of change of circumstances. Accordingly, this paper analyzes comparatively the doctrines and provisions related to renegotiation and adaptation of contracts of the most representative countries such as England, U.S.A., France, Germany as well as provisions CISG and soft law such as PICC. By doing so, the author makes clear which laws of instruments is more flexible or acceptable in allowing renegotiation and adaptation of long-term commercial contracts, and emphasizes on the importance of inclusion of express terms by using other alternative supplementing clauses, as a best solution for settling the problems of legal uncertainty of contract in relation to renegotiation and adaptation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.39-42
• /
• 1998

This paper proposes an adaptive fuzzy control scheme for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty is either unknown or impossible. In order to improve robustness under approximation errors and disturbances the proposed scheme includes deadzone in adaptation laws which varies its size adaptively. The assumption of known bounds on the approximation errors and disturbances is not required since those are estimated using adaptation laws. The overall adaptive scheme is proven to guarantee uniform ultimate boundedness in the Lyapunov sense.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.2
• /
• pp.98-106
• /
• 2013

This paper proposes fault tolerant control laws using sliding mode control and adaptation laws for a satellite with reaction wheel faults. Considering system parameter errors and faults uncertainties in the dynamics of satellite, the control laws were designed. It was assumed that only reaction wheel failures occurred as faults. The reaction wheel faults were reflected in the multiply form. Because the proposed control laws satisfy the Lyapunov stability theorem, the stability is guaranteed. Through computer simulation, it was assured that the proposed adaptive sliding mode controller has a better performance than the existing sliding mode controller under unstable angular rates.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.11
• /
• pp.963-967
• /
• 2000

This paper deals with a sliding mode control with uncertainty adaptation for the robust stabilization of input-delay systems with unknown uncertainties. A sliding surface including a state predictor is employed to compensate for the effect of the input delay. The proposed method does not need a priori knowledge of upper bounds on the norm of uncertainties, but estimates those upper bounds by adaptation laws based on the sliding surface. Then, a robust control law with the uncertainty adaptation is derived to ensure the existence of the sliding mode. A numerical example is given to illustrate the design procedure.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.67.2-67
• /
• 2001

In the adaptive fuzzy sliding mode control, from a set of fuzzy IF-THEN rules adaptive fuzzy sliding mode control whose parameters are adjusted on-line according to some adaptation laws is constructed for the purpose of controlling the plant to track a desired trajectory. Most of the research works in nonlinear controller design using fuzzy systems consider the affine system with fixed grid-rule structure based on system state availability. The fixed grid-rule structure makes the order of the controller big unnecessarily, hence the on-line fuzzy rule structure and fuzzy observer based adaptive fuzzy sliding mode controller is proposed to solve system state availability problems. Therefore adaptive laws of fuzzy parameters ...

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2308-2310
• /
• 2001

In the adaptive fuzzy sliding mode control, from a set of a fuzzy IF-THEN rules adaptive fuzzy sliding mode control whose parameters are adjusted on-line according to some adaptation laws is constructed for the purpose of controlling the plant to track a desired trajectory. Most of the research works in nonlinear controller design using fuzzy systems consider the affine system with fixed grid-rule structure based on system state availability. The fixed grid-rule structure makes the order of the controller big unnecessarily, hence the on-line fuzzy rule structure and fuzzy observer based adaptive fuzzy sliding mode controller is proposed to solve system state availability problems. Therefore, adaptive laws of fuzzy parameters for state observer and fuzzy rule structure are established implying whole system stability in the sense of Lyapunov.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.12
• /
• pp.1226-1231
• /
• 2008

A design of attitude controller for a tiltrotor is presented augmenting L1 adaptive control, neural networks, and feedback linearization. The neural networks compensate for the modeling error caused by the lack of knowledge of tiltrotor dynamics while the L1 adaptive control allows high adaptation gains in adaptation laws thereby, satisfying tracking performance requirement. The efficacy of this control methodology is illustrated in high-fidelity nonlinear simulation of a tiltrotor by flying the tiltrotor in different flight modes from where the L1 adaptive controller with neural networks is originally designed for.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.158-161
• /
• 1996

A robust adaptive tracking control architecture is proposed for a class of continuous-time nonlinear dynamic systems for which an explicit linear parameterization of the uncertainty in the dynamics is either unknown or impossible. The architecture employs an adaptive fuzzy system to compensate for the uncertainty of the plant. In order to improve the robustness under approximation errors and disturbances, the proposed architecture includes deadzone in adaptation laws. Unlike the previously proposed schemes, the magnitude of approximate errors and disturbances is not required in the determination of the deadzone size, since it is estimated using the adaptation law. The proposed algorithm is proven to be globally stable in the Lyapunov sense, with tracking errors converging to the proposed architecture.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.739-744
• /
• 2004

This paper presents an adaptive approach to control the amount of slip of the torque converter bypass clutch using its estimated friction coefficient. The proposed approach can be readily implemented using the inexpensive speed sensors currently installed in an automobile. A measurement feedback control law to drive the slip error to zero together with an adaptation law to identify the unknown friction coefficient is developed using the Lyapunov control design method. The robustness of the control and adaptation laws to parametric and/or torque uncertainties as well as the convergence of the friction coefficient are investigated. Simulation results verify the viability of the proposed control algorithm in real-world vehicle control applications.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.937-942
• /
• 1993

This paper extends the authors' prior work on the regulation of flexible space structures via partial feedback linearization (PFL) methods to articulated systems. Recursive relations introduced by Jain and Rodriguez are central to the efficient formulation of models via Poincare's form of Lagrange's equations. Such models provide for easy construction of feedback linearizing control laws. Adaptation is shown to be an effective way of reducing sensitivity to uncertain parameters. An application to a flexible platform with mobile remote manipulator system is highlighted.