Rollover prediction and control in heavy vehicles via recurrent neural networks
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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.
author list (cited authors)
Sanchez, E. N., Ricalde, L. J., Langari, R., & Shahmirzadi, D.