Artificial neural networks to control braking moments on wheels of an articulated vehicle

Author

Adamiec-Wójcik, Iwona ; Brzozowski, Krzysztof ; Warwas, Kornel

Author_Institution

Univ. of Bielsko-Biala, Bielsko-Biala, Poland

fYear

2009

fDate

21-23 Sept. 2009

Firstpage

303

Lastpage

307

Abstract

The paper presents an application of artificial neural networks to control braking moments on wheels of an articulated vehicle in a critical situation. The trajectory of the articulated vehicle was calculated for given braking moments by means of the 3D computational model. Dynamic optimization was performed in order to use appropriate values of braking moments for each wheel of the vehicle. Solutions of the optimization tasks for different inputs formed a set of optimal values. In the next step the set of optimal values was used for training an artificial neural network. Results of the calculations with the Nelder-Mead method and for the MLP and RBF neural networks are presented.

Keywords

braking; learning (artificial intelligence); learning systems; multilayer perceptrons; neurocontrollers; optimisation; radial basis function networks; road vehicles; stability; wheels; 3D computational model; MLP neural network; Nelder-Mead method; RBF neural network; articulated vehicle trajectory; artificial neural network training; braking moment control; critical situation; dynamic optimization; stability; wheel; Artificial neural networks; Computational modeling; Conferences; Road safety; Road vehicles; Stability; Testing; Vehicle dynamics; Vehicle safety; Wheels; artificial neural network; control; mathematical model; optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on

Conference_Location

Rende

Print_ISBN

978-1-4244-4901-9

Electronic_ISBN

978-1-4244-4882-1

Type

conf

DOI

10.1109/IDAACS.2009.5342974

Filename

5342974