• 대한전자공학회논문지TC
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• 제43권2호
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• pp.39-43
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• 2006

본 논문은 잡음이 존재하는 미지 시스템 출력 신호의 3차 통계치인 cumulant를 이용한 AR 식별에 관한 것이다. 미지 시스템 식별을 위한 알고리즘에서는 Parametric Modeling 기법중에서 Global Convergence 보장 및 시스템의 진폭과 위상 정보를 모두 표현할 수 있는 Cumulant를 이용한 AR (Auto Regressive) 식별 방법을 적용하였다. 식별 과정에서 미지 시스템을 하나의 AR 시스템으로 간주하였고 입력 신호를 발생하여 이를 통과시킨 후 잡음이 부가된 출력 신호를 얻어 이를 이용하였다. 신호대 잡음비의 변화에따른 AR 시스템의 식별을 수행한 결과 원래의 시스템 출력치와 유사한 양호한 식별 결과를 얻을 수 있었고 극점이 z 변환의 단위원내에 존재함을 확인하였다.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.291-304
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• 2015

Compared with the identification of linear structures, it is more challenging to conduct identification of nonlinear structure systems, especially when the locations of structural nonlinearities are not clear in structural systems. Moreover, it is highly desirable to develop methods of parametric identification using partial measurements of structural responses for practical application. To cope with these issues, an identification method is proposed in this paper for the detection and parametric identification of structural nonlinear restoring forces using only partial measurements of structural responses. First, an equivalent linear structural system is proposed for a nonlinear structure and the locations of structural nonlinearities are detected. Then, the parameters of structural nonlinear restoring forces at the locations of identified structural nonlinearities together with the linear part structural parameters are identified by the extended Kalman filter. The proposed method simplifies the identification of nonlinear structures. Numerical examples of the identification of two nonlinear multi-story shear frames and a planar nonlinear truss with different nonlinear models and locations are used to validate the proposed method.

• Structural Monitoring and Maintenance
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• 제4권1호
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• pp.33-52
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• 2017

A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.

• 안보군사학연구
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• 통권1호
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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.

• 한국생산제조학회지
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• 제21권2호
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• pp.324-330
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• 2012

In this paper, we presents a robust control system design for compensating hysteresis of a piezoelectric actuator-based actuation unit. First, the dynamics between the input voltage and the output displacement of the actuation unit are unravelled via a non-parametric system identification method. From the dynamic characteristics of those experimental transfer functions, a parametric model is then derived, whose dynamics match those of the non-parametric ones under various conditions on input voltages. A robust controller is constructed on the basis of this parametric model in order not only to effectively compensate the hysteresis of the actuation unit but also to guarantee the robust stability. Extensive experiments show that the proposed robust control system successfully mitigate the effect of the hysteresis and improve the tracking capability of the actuation unit.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.927-930
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• 1992

VSS identification approach is based on following concept, i.e. while in sliding motion, the switching of control inputs refects system uncertainites. Therefore, if there exist some operations that make the information form the switiching control inputs be achievable, then the unknown parameters can be actually identification mechanisms which can fully make use of the available information. Two different types of VSS identifiers are taken into consideration. The first type uses adjustable model whose structure is similar to that of identified systems. From the viewpoint of contro, this type of VSS identifiers may be regraded as direct identifier vecause the identified system is handled as an open loop. On the other hand, if the identified system is controlable in the sense of VSS(sliding mode can be generated through chosing control inputs), the second type of VSS identifier, the indirect VSS identifier, can be constructed according to the linerized system strucutre while staying in sliding mode. Therefroe it can be applied to some nonlinear systems which are not linear in parametric space by general identification algorithms, whereas linear in parametric space when sliding mode is existed.

• 전기학회논문지P
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• 제52권2호
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• pp.81-84
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• 2003

This paper presents a proper rational transfer function synthesis in the continuous time system from noisy measurements. The proposed method identifies the coefficients vector of the transfer function from an overdetermined linear system that develops from rearranging the two dimensional system matrices and output vectors obtained from the observed frequency responses. By computer simulation, the performance improvement is verified.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.45.6-45
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• 2002

In this paper, a novel optimization algorithm which searches for the local minima of a given cost function is proposed using the familiar property of a binary string, and is applied to the parametric identification of a continuous-time state equation by the estimation of system parameters as well as initial state values. A simple electrical circuit severs as an example, whose precise identification results show the superiority of the proposed algorithm.

• 한국소음진동공학회논문집
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• 제26권7호
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• pp.844-850
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• 2016

This study pertains to the extraction of the road noise component of signals from a vehicle's interior noise via the traditional frequency domain and time domain system identification methods. For road noise extraction based on the frequency domain system identification method, the appropriate matrix inversion strategy is investigated and causal and non-causal impulse response filters are compared. Furthermore, appropriate data lengths for the frequency domain system identification method are investigated. In addition to the traditional road noise extraction methods based on frequency domain system identification, a new approach to extract road noise via the time domain system identification method based on a parametric input-output model is proposed and investigated in the present study. In this approach, instead of constructing a higher order model for the full-band road noise, input and output signals are processed in the subband domain and lower order parametric models optimal to each subband are determined. These parametric models are used to extract road noises in each subband; the full band road noise is then reconstructed from the subband road noises. This study shows that both the methods in the frequency domain and the time domain successfully extract the road noise from the vehicle's interior noise.

• Smart Structures and Systems
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• 제15권2호
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• pp.425-445
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• 2015

Parametric identification of structures is one of the important aspects of structural health monitoring. Most of the techniques available in the literature have been proved to be effective for structures with small degree of freedoms. However, the problem becomes challenging when the structure system is large, such as bridge structures. Therefore, it is highly desirable to develop parametric identification methods that are applicable to complex structures. In this paper, the LSE based techniques will be combined with the substructure approach for identifying the parameters of a cable-stayed bridge with large degree of freedoms. Numerical analysis has been carried out for substructures extracted from the 2-dimentional (2D) finite element model of a cable-stayed bridge. Only vertical white noise excitations are applied to the structure, and two different cases are considered where the structural damping is not included or included. Simulation results demonstrate that the proposed approach is capable of identifying the structural parameters with high accuracy without measurement noises.