• Smart Structures and Systems
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• v.23 no.3
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• pp.295-306
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• 2019

Shanghai Tower is a 632-meter super high-rise building located in an area with wind and active earthquake. A sophisticated structural health monitoring (SHM) system consisting of more than 400 sensors has been built to carry out a long-term monitoring for its operational safety. In this paper, a reduced-order model including 31 elements was generated from a full model of this super tall building. An iterative regularized matrix method was proposed to tune the system parameters, making the dynamic characteristic of the reduced-order model be consistent with those in the full model. The updating reduced-order model can be regarded as a benchmark model for further analysis. A long-term monitoring for structural dynamic characteristics of Shanghai Tower under different construction stages was also investigated. The identified results, including natural frequency and damping ratio, were discussed. Based on the data collected from the SHM system, the dynamic characteristics of the whole structure was investigated. Compared with the result of the finite element model, a good agreement can be observed. The result provides a valuable reference for examining the evolution of future dynamic characteristics of this super tall building.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.812-818
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• 2017

In this paper, we design a reduced-order disturbance observer (DOB) controller for an EMS (Electro-Magnetic Suspension) system with mass uncertainty. Compared with conventional DOB controller, the proposed reduced-order DOB controller can be implemented in a simpler way, since it uses reduced order nominal model and Q-filter. It is shown that the nominal model for the proposed DOB controller should be carefully chosen in order to achieve the robust stability in the present of mass uncertainty. Computer simulation results to validate the effectiveness of the proposed DOB controller are included.

• East Asian mathematical journal
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• v.34 no.5
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• pp.661-681
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• 2018

In this paper, we discuss a reduced-order modeling for the Benjamin-Bona-Mahony-Burgers (BBMB) equation and its application to a distributed feedback control problem through the centroidal Voronoi tessellation (CVT). Spatial distcritization to the BBMB equation is based on the finite element method (FEM) using B-spline functions. To determine the basis elements for the approximating subspaces, we elucidate the CVT approaches to reduced-order bases with snapshots. For the purpose of comparison, a brief review of the proper orthogonal decomposition (POD) is provided and some numerical experiments implemented including full-order approximation, CVT based model, and POD based model. In the end, we apply CVT reduced-order modeling technique to a feedback control problem for the BBMB equation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4411-4417
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• 2012

The present study proposes the optimization of wing structure base on reduced model which assures the solution accuracy and computational efficiency. Well-constructed reduced model assures the accurate result in the eigenvalue problem, dynamic analysis or sensitivity of design optimization. Reduced system is classified into the reduce-order model based on structural modes and the reduced system based on degrees of freedom. Because this study uses the reduced system based on degrees of freedom, it is important to select the dominant degrees of freedom properly. For this work, robust selection method, two-level selection scheme, is employed and IRS(Improved Reduced System) is applied to construct the final reduced system. In the optimization process based on the reduced system, all of the equivalent stress, eigenvalue and design sensitivities are calculated from the reduced system. Through a numerical example, it is shown that the present optimization methodology based on the reduction method can provide an optimal results for objective function satisfying constraint condition.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.487-493
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• 2001

In this paper, a new reduced-order dynamic observer method is presented. Two types of observers are pronounced, namely, the model based reduced-order dynamic observer and the Luenburger type reduced-order dynamic observer. Useful design algorithms are also provided for each structure. The essential features of the proposed observed design methods are addressed to be qualified ad effective observers. The proposed method clarifies the duality between the controller and observer designs.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.245-248
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• 1998

This paper proposes a sensorless velocity estimator using the reduced-order state equation of induction motor based on Kalman Filter. The electrical transients in the stator voltage equations of induction motor are neglected in the reduced-order model. The advantage of using the reduced-order model is to reduce the required number of numerical integrations for filtering the rotor speed. As changing the operating points and the parameters of the induction motor in simulation studies, the behavior of the sensorless velocity estimator as predicted by the reduced-order state equation of induction machine is compared with the behavior predicted by the complete state equation of induction machine.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.8
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• pp.584-593
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• 1987

A new combined approximation method using Routh stability array and mean-square error (MSE) method is proposed for deriving reduced-order z-transter functions for discrete time systems. The Routh stability array is used to obtain the reduced-order denominator polynomial, and the numerator polynomial is obtained by minimizing the mean-square error between the unit step responses of the original system and reduced model. The advantages of the new combined approximation method are that the reduced model is always stable provided the original model is stable and the initial and steady-state characteristics of the original model can be preserved in the reduced model.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1176-1178
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• 1998

This paper presents a model reduction procedure of the high order MIMO (multi input multi output) controller designed for the steam turbine in the generating plant. The application limit to reduction of the order is reviewed by variation in Hankel singular value as well as by variation in singular value Bode diagrams of transfer function matrices. Dynamic performances in the time domain are also compared for each reduced order model.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.439-444
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• 2002

In this paper, a new model reduction method is proposed to obtain a reduced order model in the frequency domain. The method is developed based on the second-order plus dead time modeling technique. The initial value of the reduced model parameters can be obtained using this method coinciding four point(0, -$\pi$/2, -$\pi$, -3$\pi$/2) on the Nyquist curve. The optimal parameters of the reduced model is obtained through calculation procedure with three steps. It is shown that Nyquist curves and unit step responses of the reduced models of numerical examples closely agree with those of original models.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.8-17
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• 2019

In this study, a model reduction technique was used to develop a precise noise and vibration prediction model for the individual components of a driveline system. The dynamic reduced-order model generated by the Craig-Bampton method was applied to perform dynamic analysis of an electric agricultural power cart. The natural frequency and acceleration response results were analyzed according to the different number of dominant sub-structural modes contained in the reduced-order models. Through the analysis results, it was confirmed that a sufficient number of dominant sub-structures to satisfy the operating conditions should be selected to construct an optimal reduced-order model.