Brown, R., Mazza, M., Le, D., and Murugan, M., "Comparison of Generalized Predictive Control Algorithms Using a Full Vehicle Multi-Body Dynamics Model," SAE Technical Paper 2012-01-1932, 2012, doi:10.4271/2012-01-1932.
This paper discusses research conducted by the U.S. Army Research Laboratory (ARL) - Vehicle Technology Directorate (VTD) on advanced suspension control. ARL-VTD has conducted research on advanced suspension systems that will reduce the chassis vibration of ground vehicles while maintaining tire contact with the road surface. The purpose of this research is to reduce vibration-induced fatigue to the Warfighter as well as to improve the target aiming precision in-theater.The objective of this paper was to explore the performance effectiveness of various formulations of the Generalized Predictive Control (GPC) algorithm in a simulation environment. Each version of the control algorithm was applied to an identical model subjected to the same ground disturbance input and compared to a baseline passive suspension system. The control algorithms considered include a GPC with Implicit Disturbances, GPC with Explicit Disturbances, and GPC with Preview Control. A two-axle tactical vehicle with independent front and rear suspensions was modeled in the TruckSim full-vehicle dynamics simulator. The control algorithms were compared based on their effectiveness in controlling peak acceleration and overall average acceleration over a range of vehicle speeds. The algorithms demonstrated significant reductions in the chassis acceleration and pitch of the full-vehicle model.