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Title: Parametric identification of vehicle handling using an extended Kalman filter
Authors: Best, Matt C.
Keywords: Vehicle handling dynamics
Kalman filter
System identification
Vehicle parameter
Issue Date: 2007
Publisher: © Inderscience Publishers
Citation: BEST, M.C., 2007. Parametric identification of vehicle handling using an extended Kalman filter. International Journal of Vehicle Autonomous Systems, 5 (3/4), pp. 256-273.
Abstract: This paper considers a novel method for estimating parameters in a vehicle handling dynamic model using a recursive filter. The well known extended Kalman filter – which is widely used for real-time state estimation of vehicle dynamics – is used here in an unorthodox fashion; a model is prescribed for the sensors alone, and the state vector is replaced by a set of unknown model parameters. With the aid of two simple tuning parameters, the system self-regulates its estimates of parameter and sensor errors, and hence smoothly identifies optimal parameter choices. In a linear-in-the-parameters example, the results are shown to be comparable to least-squares identification, but the system works equally well for the more general nonlinear handling model examples, and should be well suited to any smoothly nonlinear system. Moreover, it is shown that by simple adjustment of the tuning parameters the filter can operate in a real-time capacity.
Version: Accepted for publication
DOI: 10.1504/IJVAS.2007.016404
URI: https://dspace.lboro.ac.uk/2134/8317
Publisher Link: http://dx.doi.org/10.1504/IJVAS.2007.016404
ISSN: 1741-5306
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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