Rollover prediction and control in heavy vehicles via recurrent neural networks Conference Paper

abstract

• A state predictor is developed in order to estimate roll angle and lateral acceleration for tractor-semitrailers. Based on this prediction, an active control system is designed to prevent rollover. In order to develop this control structure, 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. Via simulations, the control scheme is applied for speed-yaw rate trajectory tracking in a tractor-semitrailer during a cornering situation.

authors

• Langari, Gholamreza

published proceedings

• Proceedings of the IEEE Conference on Decision and Control

author list (cited authors)

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

complete list of authors

• Sanchez, EN||Ricalde, LJ||Langari, R||Shahmirzadi, D

publication date

• December 2004

published in

• IEEE Conference on Decision and Control  Journal

start page

• 5210

end page

• 5215

volume

• 5