Recurrent Neural Control for Rollover Prevention on Heavy Vehicles Conference Paper

abstract

• An active control system is developed to prevent rollover in heavy vehicles. A high order recurrent neural network is used to model the unknown tractor semitrailer system; a learning law is obtained using the Lyapunov methodology. Then a control law, which stabilizes the reference tracking error dynamics, is developed using Control Lyapunov Functions. The control scheme is applied to the speed and speed-yaw rate trajectory tracking in a tractor-semitrailer during a cornering situation.

name of conference

• 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)

authors

• Langari, Gholamreza

published proceedings

• 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)

author list (cited authors)

• Sanchez, E. N., Ricalde, L. J., Langari, R., & Shahmirzadi, D.

citation count

• 2

complete list of authors

• Sanchez, Edgar N||Ricalde, Luis J||Langari, Reza||Shahmirzadi, Danial

publication date

• January 2004

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Conference on Neural Networks - Conference Proceedings  Journal

keywords

• Neurosciences
• Prevention

Digital Object Identifier (DOI)

• 10.1109/ijcnn.2004.1380889

International Standard Book Number (ISBN) 10

• 0780383591

start page

• 1841

end page

• 1846

volume

• 3

URL

• http://dx.doi.org/10.1109/ijcnn.2004.1380889

user-defined tag

• 3 Good Health and Well-Being