Analytical Evaluation of Generalized Predictive Control Algorithms Using a Full Vehicle Multi-Body Dynamics Model For Mobility Enhancement

ABSTRACT: 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<br>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<br>environment. Each version of the control algorithm was applied to an identical model subjected to the same<br>ground disturbance input and compared to a baseline passive suspension system. The control algorithms<br>considered include a GPC with Implicit Disturbances, GPC with Explicit Disturbances, and GPC with Preview<br>Control. A two-axle tactical vehicle with independent front and rear suspensions was modeled in the TruckSim<br>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. Keywords: Vehicle vibration control, vehicle dynamics simulation, control algorithm, advanced suspension, generalized predictive control.