• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.624-627
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• 2002

Experimental study showed that the existing mathematical model doesn't fully describe the lateral motion of a moving web fur different operating conditions. So, a physically interpretable model of lateral motion of a moving web in a typical web guidance system, operated at Konkuk Univ., was developed using the system identification technique. A well-known Least Square Method based on ARX model was used for the system identification. Lateral displacement of the web was measured at the exit of each span by infrared sensors. The model obtained from identifying a linear time-invariant system for a typical operating condition yields an improved prediction capability of the lateral dynamics of the moving web compared to other mathematical models proposed in literature.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1412-1415
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• 1996

In this paper, a new identification method of the cascade control system is proposed which can overcome the weak points of Krishnaswamy and Rangaiah(1987)'s method. This new method consists of two steps. One is on-line process identification using the numerical integration to approximate the two process dynamics with a high order linear transfer function. The other is a model reduction technique to derive out low order transfer function(FOPTD or SOPTD) from the obtained high order linear transfer function to tune the controller using usual tuning rules. While the proposed method preserves the advantages of the Krishnaswamy and Rangaiah(1987)'s method, it has such a simplicity that it requires only measured input and output data and simple least-squares technique. Simulation results show that the proposed method can be a promising alternative in the identification of cascade control systems.

• Journal of National Security and Military Science
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• s.1
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• pp.191-229
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• 2003

Multi-sensor data fusion techniques combine evidences from multiple sensors in order to get more accurate and efficient meaningful information through several process levels that may not be possible from a single sensor alone. One of the most important parts in the data fusion system is the identification fusion, and it can be categorized into physical models, parametric classification and cognitive-based models, and parametric classification technique is usually used in multi-sensor data fusion system by its characteristic. In this paper, we propose a novel heuristic identification fusion method in which we adopt desirable properties from not only parametric classification technique but also cognitive-based models in order to meet the realtime processing requirements.

• 한국기계연구소 소보
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• s.10
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• pp.35-48
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• 1983

When the hydrodynamic coefficients of the ship maneuvering equation are estimated by captive model test, it is difficult to take account of the scale effect between model and full scale ship. This scale effect problem can be overcome by processing the sea trial data with system identification. Extended Kalman filter is used as a system identification technique for the modification of the simulation equation as well as the estimation of hydrodynamic coefficients. The phenomena of simultaneous drifting of linear coefficients occur. It is confirmed that two coefficients in each pair-($Y_v$', $Y_r$' -m' u'), ($N_v$', $N_r$' )-are simultaneously drifting and all 4 coefficients are simultaneously drifting together. Particularly simultaneous drifting of 2 coefficients in each pair is more significant. It is also shown that the simultaneous drifting of 4 coefficients can be reduced by choosing the input data which have the random v'/r' curve and 4 coefficients are estimated within 2-4% error, which may be noise level. So, it is recommended to operate the rudder randomly in sea trial or model test for the application of system identification technique.

• Structural Engineering and Mechanics
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• v.22 no.1
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• pp.53-70
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• 2006

The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50's. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.04a
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• pp.3-7
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• 1991

Considering the relatively large amount of stable flexural teat results available for steel fiber reinforced concrete (SFRC) and their dependency on the constitutive behavior of the material, a technique called “System Identification” is used for interpretating the flexural test data in order to obtain basic information on the tensile constitutive behavior of steel fiber reinforced concrete. “System Identification” was successful in obtaining optimum sets of parameters which provide satisfactory matches between the measured and predicted flexural load-deflection relationships.

• Bulletin of the Society of Naval Architects of Korea
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• v.21 no.4
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• pp.10-20
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• 1984

When the hydrodynamic coefficients of the ship maneuvering equation are estimated by captive model test, it is difficult to take account of the scale effect between model and full scale ship. This scale effect problem can be overcome by processing the sea trial data with system identification. Extended Kalman filter is used as a system identification technique for the modification of the simulation equation as well as the estimation of hydrodynamic coefficients The phenomena of simultaneous drifting of linear coefficients occur. It is confirmed that two coefficients in each pair-$(Y_v',\;Y_r'-m'u'),\;(N_v',\;N_r')$-are simultaneously drifting and all 4 coefficients are drifting together. Particularly simultaneous drifting and 2 coefficients in each pair is more significant. It is also shown that the simultaneous drifting of 4 coefficients can be reduced by choosing the input data which have the random v'/r' curve and 4 coefficients are estimated within $2{\sim}4%$ error, which may be noise level. So, it is recommended to operate the rudder randomly in sea trial or model test for the application of system identification technique.

• Computational Structural Engineering
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• v.10 no.2
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• pp.149-160
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• 1997

Mechanical structures are composed of substructures connected by joints and boundary elements. While the finite element representation of plain substructures is well developed and reliable, joints have a lot of uncertainties in being accurately modelled and affect dynamic behavior of a total system. In order to improve the accuracy of a finite element model, a new method is proposed, in which reduced finite element model is combined with a system identification technique. After substructures except joints are modelled with finite element method and joint properties are represented by parameter states, non-linear state equation is derived in which parameter states are multiplied by physical states such as displacements and velocities. So the joint parameter identification is transformed into non-linear state estimation problem. The methods are tested and discussed numerically and the feasibility for physical application has been demonstrated through two example structures.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.71-81
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• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.