Comparison of Performance Effectiveness of Generalized Predictive Control Algorithms Developed for a Simplified Ground Vehicle Suspension System

This paper discusses the research conducted by the 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 algorithm in a simulation environment. Each version of the control algorithm was applied to an identical model subjected to the same disturbance input and compared to a baseline passive suspension system. The control algorithms considered include a Generalized Predictive Controller (GPC) with Implicit Disturbances, GPC with Explicit Disturbances, and GPC with Preview Control. The suspension model used was a two-degree-of-freedom (2 DOF) quarter car model with a given set of vehicle parameters. The performance of the developed control algorithms were compared based on their effectiveness in controlling peak acceleration and overall average acceleration through a range of vehicle speed. The algorithms demonstrated significant improvements in the chassis acceleration of the quarter-car model.