A randomized integral error criterion for parametric identification of dynamic models of mechanical systems

Best, M. C. and Gordon, T. J. (1999) A randomized integral error criterion for parametric identification of dynamic models of mechanical systems. Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering, 213 (2). pp. 119-134. ISSN 0959-6518

Full content URL: http://dx.doi.org/10.1243/0959651991540430

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Item Type:Article
Item Status:Live Archive


This paper proposes a new approach to the identification of reduced order models for complex mechanical vibration systems. Parametric identification is commonly conducted by the regression of time-series data, but when this includes significant unmodelled modes, the error process has a high variance and autocorrelation. In such cases, optimization using least-squares methods can lead to excessive parameter bias. The proposed method takes advantage of the inherent boundedness of mechanical vibrations to design a new regression set with dramatically reduced error variance. The principle is first demonstrated using a simple two-mass simulation model, and from this a practicable approach is derived. Extensive investigation of the new randomized integral error criterion method is then conducted using the example of identification of a quarter-car suspension system. Simulation results are contrasted with those from comparable direct least-squares identifications. Several forms of the identification equations and error sources are used, and in all cases the new method has clear advantages, both in accuracy and consistency of the resulting identification model. © IMechE 1999.

Keywords:Computer simulation, Error analysis, Mathematical models, Random processes, Regression analysis, Time series analysis, Error processes, Mechanical systems, Parametric identification, Integral equations
Subjects:H Engineering > H660 Control Systems
H Engineering > H330 Automotive Engineering
Divisions:College of Science > School of Engineering
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ID Code:11681
Deposited On:01 Oct 2013 17:45

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