Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation

Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation

This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a...

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Bibliographic Details
Main Author: Rhode, Stephan (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2018
Series:Karlsruher Schriftenreihe Fahrzeugsystemtechnik / Institut für Fahrzeugsystemtechnik
Subjects:
Technology: general issues
Total Least Squares
errors-in-variables
robust estimation
Onlinefilter
recursive estimation
Robuste Schätzer
Systemidentifikation
system identification
Online Access:DOAB: download the publication
DOAB: description of the publication
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Description
Summary:This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models.
Physical Description:1 electronic resource (XXIV, 196 p. p.)
ISBN:KSP/1000083492
9783731508076
Access:Open Access

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