Name
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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/CDC.2004.1429635 | Decision and Control, 2004. CDC. 43rd IEEE Conference |
Keywords | DocType | Volume |
lyapunov methods,agricultural machinery,learning (artificial intelligence),neurocontrollers,recurrent neural nets,active control system,control lyapunov functions,cornering,heavy vehicles,lateral acceleration,learning law,recurrent neural network,reference tracking error dynamics,roll angle,rollover control,rollover prediction,simulations,speed-yaw rate trajectory tracking,state predictor,tractor-semitrailers,learning artificial intelligence,control lyapunov function,control structure | Conference | 5 |
ISSN | ISBN | Citations |
0191-2216 | 0-7803-8682-5 | 4 |
PageRank | References | Authors |
1.12 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanchez, Edgar N. | 1 | 78 | 9.09 |
| Ricalde, Luis J. | 2 | 4 | 1.12 |
| Langari, R. | 3 | 6 | 1.54 |
| Shahmirzadi, Danial | 4 | 4 | 1.12 |