Abstract:

This paper describes an approach to the vehicle rollover prevention problem that includes estimation of parameters affecting the roll dynamics and a controller accounting for uncertainties in such parameters. We develop an adaptive reference governor (ARG) that modifies the driver steering input based on satisfaction of a rollover avoidance constraint, and state and input constraints. The vehicle dynamics are highly nonlinear and has parametric uncertainties, for which the presented approach ensures rollover prevention. We design a recursive Bayesian estimator that produces confidence estimates of the parameters, including the center-of-gravity height. The confidence estimates are used to construct online constraint admissible sets, which are leveraged by the ARG to ensure rollover prevention. Simulation results on a Fishhook maneuver show that the method robustly avoids rollover prevention, and that the resulting parameter estimates are contained in the confidence sets.