TY - GEN
T1 - Multi-objective coordinated control for advanced adaptive cruise control system
AU - Li, Shengbo
AU - Li, Keqiang
AU - Rajamani, Rajesh
AU - Wang, Jianqiang
PY - 2009/12/1
Y1 - 2009/12/1
N2 - This paper presents a MPC theory based Multi-Objective Vehicular Adaptive Cruise Control system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is designed using model predictive control theory. A cost function is developed that considers the contradictions between tracking error, fuel consumption and driver characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as I/O constraints. Employing a "constraint softening" method to avoid computing infeasibility problems, a control law is developed and implemented using a numerical optimization algorithm. Detailed simulations show that the developed control system provides significant benefits in terms of fuel economy, vehicle safety and tracking capability while at the same time also satisfying driver desired car following characteristics.
AB - This paper presents a MPC theory based Multi-Objective Vehicular Adaptive Cruise Control system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is designed using model predictive control theory. A cost function is developed that considers the contradictions between tracking error, fuel consumption and driver characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as I/O constraints. Employing a "constraint softening" method to avoid computing infeasibility problems, a control law is developed and implemented using a numerical optimization algorithm. Detailed simulations show that the developed control system provides significant benefits in terms of fuel economy, vehicle safety and tracking capability while at the same time also satisfying driver desired car following characteristics.
UR - http://www.scopus.com/inward/record.url?scp=77950813931&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950813931&partnerID=8YFLogxK
U2 - 10.1109/CDC.2009.5400863
DO - 10.1109/CDC.2009.5400863
M3 - Conference contribution
AN - SCOPUS:77950813931
SN - 9781424438716
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3539
EP - 3544
BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
T2 - 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Y2 - 15 December 2009 through 18 December 2009
ER -