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A new linear parametrization for peak friction coefficient estimation in real time

Title
A new linear parametrization for peak friction coefficient estimation in real time
Type
Article in International Conference Proceedings Book
Year
2010
Authors
Ricardo de Castro
(Author)
FEUP
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Rui Esteves Araújo
(Author)
FEUP
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Jaime S. Cardoso
(Author)
FEUP
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Diamantino Freitas
(Author)
FEUP
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Conference proceedings International
Initial page: 6 pag.
IEEE Vehicle Power and propulsion Conference
Lille, France, 1-3, September
Indexing
INSPEC
Scientific classification
FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering
CORDIS: Technological sciences > Engineering > Control engineering ; Technological sciences > Technology > Energy technology > Electric vehicles
Other information
Authenticus ID: P-007-XY6
Abstract (EN): The correct estimation of the friction coefficient in automotive applications is of paramount importance in the design of effective vehicle safety systems. In this article a new parametrization for estimating the peak friction coefficient, in the tire-road interface, is presented. The proposed parametrization is based on a feedforward neural network (FFNN), trained by the Extreme Learning Machine (ELM) method. Unlike traditional learning techniques for FFNN, typically based on backpropagation and inappropriate for real time implementation, the ELM provides a learning process based on random assignment in the weights between input and the hidden layer. With this approach, the network training becomes much faster, and the unknown parameters can be identified through simple and robust regression methods, such as the Recursive Least Squares. Simulation results, obtained with the CarSim program, demonstrate a good performance of the proposed parametrization; compared with previous methods described in the literature, the proposed method reduces the estimation errors using a model with a lower number of parameters.
Language: English
Type (Professor's evaluation): Scientific
Contact: raraujo@fe.up.pt
No. of pages: 6
License type: Click to view license CC BY-NC
Documents
File name Description Size
95-60513-final 275.66 KB
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