Title :
Recurrent neural control for rollover prevention on heavy vehicles
Author :
Sanchez, Edgar N. ; Ricalde, Luis J. ; Langari, Reza ; Shahmirzad, Danial
Author_Institution :
CINVESTAV, Unidad Guadalajara, Jalisco, Mexico
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.
Keywords :
Lyapunov methods; agricultural machinery; neurocontrollers; position control; recurrent neural nets; road vehicles; velocity control; active control system; control Lyapunov function; heavy vehicles; high order recurrent neural network; learning law; recurrent neural control; rollover prevention; speed control; speed-yaw rate trajectory tracking; tracking error dynamics; tractor semitrailer system; Adaptive control; Control systems; Nonlinear control systems; Optimal control; Recurrent neural networks; Sliding mode control; Trajectory; Uncertainty; Vehicle dynamics; Velocity control;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380889
