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  • 1
    Electronic Resource
    Electronic Resource
    An experimental study of nonlinear dynamic system identification (1992)
    Springer
    Nonlinear dynamics 3 (1992), S. 1-11 
    Details
    ISSN: 1573-269X
    Keywords: Identification technique ; nonlinear dynamic systems ; identification from noisy measurements ; vibration ; two-point boundary-value problem
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A technique for robust identification of nonlinear dynamic systems is developed and illustrated using both digital simulations and analog experiments. The technique is based on the Minimum Model Error optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00045467
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    Paper (German National Licenses)
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  • 2
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    Model determination for nonlinear state-based system identification (2010)
    Springer
    Details
    Publication Date: 2010-09-18
    Print ISSN: 0924-090X
    Electronic ISSN: 1573-269X
    Topics: Mathematics
    Published by Springer
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    PAPER CURRENT
  • 3
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    An experimental study of nonlinear dynamic system identification (1992)
    Springer
    Details
    Publication Date: 1992-01-01
    Print ISSN: 0924-090X
    Electronic ISSN: 1573-269X
    Topics: Mathematics
    Published by Springer
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    PAPER CURRENT
  • 4
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    Scalar gain interpretation of large order filters (1993)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: A technique is developed which demonstrates how to interpret a large fully-populated filter gain matrix as a set of scalar gains. The inverse problem is also solved, namely, how to develop a large-order filter gain matrix from a specified set of scalar gains. Examples are given to illustrate the method.
    Keywords: NUMERICAL ANALYSIS
    Type: NASA. Goddard Space Flight Center, Flight Mechanics(Estimation Theory Symposium, 1992; p 507-521
    Format: application/pdf
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  • 5
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    Correlation techniques to determine model form in robust nonlinear system realization/identification (1991)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: The fundamental challenge in identification of nonlinear dynamic systems is determining the appropriate form of the model. A robust technique is presented which essentially eliminates this problem for many applications. The technique is based on the Minimum Model Error (MME) optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature is the ability to identify nonlinear dynamic systems without prior assumption regarding the form of the nonlinearities, in contrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. Model form is determined via statistical correlation of the MME optimal state estimates with the MME optimal model error estimates. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
    Keywords: NUMERICAL ANALYSIS
    Type: NASA. Goddard Space Flight Center, Flight Mechanics(Estimation Theory Symposium, 1991; p 443-459
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  • 6
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    An experimental study of nonlinear dynamic system identification (1991)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: A technique based on the Minimum Model Error optimal estimation approach is employed for robust identification of a nonlinear dynamic system. A simple harmonic oscillator with quadratic position feedback was simulated on an analog computer. With the aid of analog measurements and an assumed linear model, the Minimum Model Error Algorithm accurately identifies the quadratic nonlinearity. The tests demonstrate that the method is robust with respect to prior ignorance of the nonlinear system model and with respect to measurement record length, regardless of initial conditions.
    Keywords: SPACECRAFT DESIGN, TESTING AND PERFORMANCE
    Type: NASA. Langley Research Center, Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, Part 2; p 813-823
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  • 7
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    An experimental study of nonlinear dynamic system identification (1990)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: A technique for robust identification of nonlinear dynamic systems is developed and illustrated using both simulations and analog experiments. The technique is based on the Minimum Model Error optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in constrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.
    Keywords: ASTRODYNAMICS
    Type: NASA, Goddard Space Flight Center, Flight Mechanics(Estimation Theory Symposium, 1990; p 275-290
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  • 8
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    Optimal post-experiment estimation of poorly modeled dynamic systems (1988)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.
    Keywords: NUMERICAL ANALYSIS
    Type: NASA, Goddard Space Flight Center, Flight Mechanics(Estimation Theory Symposium 1988; p 131-152
    Format: application/pdf
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  • 9
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    An automated method of tuning an attitude estimator (1995)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.
    Keywords: ASTRODYNAMICS
    Type: NASA. Goddard Space Flight Center, Flight Mechanics(Estimation Theory Symposium 1995; p 127-135
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  • 10
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    Time domain modal identification/estimation of the mini-mast testbed (1991)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: The Mini-Mast is a 20 meter long 3-dimensional, deployable/retractable truss structure designed to imitate future trusses in space. Presented here are results from a robust (with respect to measurement noise sensitivity), time domain, modal identification technique for identifying the modal properties of the Mini-Mast structure even in the face of noisy environments. Three testing/analysis procedures are considered: sinusoidal excitation near resonant frequencies of the Mini-Mast, frequency response function averaging of several modal tests, and random input excitation with a free response period.
    Keywords: SPACECRAFT DESIGN, TESTING AND PERFORMANCE
    Type: NASA. Langley Research Center, Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, Part 2; p 825-843
    Format: application/pdf
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