• 한국해양공학회지
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• 제10권1호
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• pp.108-118
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• 1996

This paper presents automatic reentry of a deepsea reser by adaptive control. Reentry is one of the major pro blems regarding a deepsea riser. In the reentry operation, the lower end of riser must be accurately positioned over the tarket point on the seabed. But the deepsea riser shows complex elastic response due to flexibility and nonlinearity of the riser dynamics and the required positioning accuracy is high. Moreover, elastic deformation must by controlled for securing structural integrity. In adaptive control, uncertainly known parameters like added mass and drag coefficient in the riser dynamics are identified and control forces at the floating body and the riser are calculated simultaneously. An Adaptive algorithm for MIMO linear discrete time system without requiring a persistent excitation is adopted in this study. The effectiveness of adaptive control logic is tested by numerical simulation and model experiment. The designed control system shows good overall performances, so that the present study can be applied to the control of the deepsea riser.

• 한국초전도학회:학술대회논문집
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• 한국초전도학회 2003년도 High Temperature Superconductivity Vol.XIII
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• pp.35-35
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• 2003

• International Journal of Control, Automation, and Systems
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• 제3권3호
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• pp.387-396
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• 2005

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust $H_\infty$ control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities, due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

• 대한기계학회논문집A
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• 제24권6호
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• pp.1633-1642
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• 2000

Like many other mechanical dynamic systems, flexible manipulator systems experience stiction or sticking friction, which may cause input-dependent instabilities. Manipulator performance can be enha nced by identifying friction but it is hard and expensive to measure friction by direct and precise sensing of contact displacements and forces. This study addresses the problem of identifying flexible manipulator joint friction. A dynamic model of a two-link flexible manipulator based upon finite element and Lagrange's method is constructed. The dynamic model includes the effects of joint compliances and actuator dynamics. Friction is also incorporated in the dynamic model to account for stick-slip at the joints. Next, the friction parameters are to be determined. The identification problem is posed as an optimization problem to be solved using nonlinear programming methods. A genetic algorithm is used to increase the convergence rate and the chances of finding the global optimum. The identified friction parameters are experimentally verified and it is expected that the identification technique is applicable to a system parameter identification problem associated with a wide class of nonlinear systems.

• 융합신호처리학회논문지
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• 제6권1호
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• pp.45-52
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• 2005

동적 신경망은 temporal 신호처리가 요구되는 여러 분야에 사용되어 왔다. 본 논문에서는 다층 리커런트 신경망(RNN)의 동특성을 더 향상시키기 위해 지역 궤환 신경망(LRNN)과 광역 궤환 신경망(GRNN)으로 구성된 합성 신경망을 사용하여 시스템 식별을 다루고 있다. 합성 신경망의 구조는 LRNN으로 IIR-MLP를, GRNN으로 Elman RNN을 결합하고 있다. 합성신경망은 선형과 비선형 시스템 식별을 통해 평가되었으며 상대적인 성능평가를 위해 Elman RNN과 IIR-MLP 신경망과 비교하고 있다. 시뮬레이션 결과에 의하면 합성 신경망은 학습속도와 정확도에서 더 우수하게 동작하였으며, 이러한 사실은 비선형 시스템 식별에 있어서 합성 신경망이 기존의 다층 리커런트 신경망보다 더 효과적인 신경망이 될 수 있음을 보여주었다.

• International Journal of Aeronautical and Space Sciences
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• 제7권2호
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• pp.121-127
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• 2006

An analysis procedure for the combined problem of control algorithm and aeroelastic system which is based on the computational fluid dynamics(CFD) technique has been developed. The aerodynamic forces in the transonic region are calculated from the transonic small disturbance(TSD) theory. An linear quadratic regulator(LQR) controller is designed to suppress the transonic flutter. The optimal control gain is estimated by solving the discrete-time Riccati equation. The system identification technique rebuilds the CFD-based aeroelstic system in order to form an adequate system matrix which involved in the discrete-time Riccati equation. Finally the controller, that is constructed on the basis of system identification technique, is used to suppress the flutter phenomenon of the airfoil with attached store. This approach, that is, the CFD-based aeroservoelasticity design, can be utilized for the development of effective flutter controller design in the transonic region.

• Earthquakes and Structures
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• 제6권4호
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• pp.393-408
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• 2014

In this paper, a direct identification of modal parameters using the continuous wavelet transform is proposed. The purpose of this method is to transform the differential equations of motion into a system of algebraic linear equations whose unknown coefficients are modal parameters. The efficiency of the present method is confirmed by numerical data, without and with noise contamination, simulated from a discrete forced system with four degrees-of-freedom (4DOF) proportionally damped.

• 대한기계학회논문집B
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• 제24권3호
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• pp.354-362
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• 2000

This paper identifies a discrete-time linear combustion model of Refuse Incineration Plant(RIP) which characterizes steam generation quantity, where the RIP is considered as a MIMO system with thirteen-inputs and one-output. The structure of RIP model is described as an ARX model which are analytically obtained from the combustion dynamics. Furthermore, using the Instrumental Variable(IV) identification algorithm, model structure and unknown parameters are identified from experimental input-output data sets, In result, it is shown that the identified ARX model well approximates the input-output combustion characteristics given by experimental data sets.

• 동력기계공학회지
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• 제3권2호
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• pp.34-41
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• 1999

This paper identifies a linear combustion model of Refuse Incineration Plant(RIP) which characterizes its combustion dynamics, where the proposed model has thirteen-inputs and one-output. The structure of the RIP model is given as an ARX model which obtained from the theoretical analysis. And then, some unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. In result, it is shown that the proposed model well approximates the input-output combustion characteristics riven by experimental data sets.

• Smart Structures and Systems
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• 제13권5호
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• pp.821-848
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• 2014

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.