Recurrent Neural Control for Rollover Prevention on Heavy Vehicles
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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.
author list (cited authors)
Sanchez, E. N., Ricalde, L. J., Langari, R., & Shahmirzadi, D.