Lateral stability analysis and MPC tracking control for articulated heavy vehicles

Abstract

Articulated heavy vehicles (AHVs) exhibit poor maneuverability during curved-path negotiations and low lateral stability under high-speed evasive maneuvers, which may lead to unstable motion modes, e.g., trailer-sway and jackknifing, causing severe accidents. However, vehicle parameters that can improve the static stability may degrade the dynamic stability. Therefore, to design controllers for improving the stability of AHVs, the trade-off between the static and dynamic instabilities is a necessary research topic. To analyze this trade-off, three different trailer payload schemes and two different tractor rear axle arrangements are considered. This trade-off is quantified using numerical simulations. Building upon the above trade-off analysis, this study designs an active safety technique in terms of a tracking-controller based on nonlinear model predictive control (NLMPC) for autonomous AHVs. With the proposed tracking-controller, the AHV tracks the predefined reference path and follows a planned forward speed scheme. Numerical simulation demonstrates the effectiveness of the proposed NLMPC tracking-controller.