Name
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 parameter estimation. We develop a parameter-adaptive reference governor (PARG) that modifies the driver steering input to enforce a rollover avoidance constraint, and state and input constraints. We design a recursive Bayesian estimator that produces confidence estimates of the parameters, including the center-of-gravity height. The confidence estimates inform a supervised learning algorithm, which constructs online constraint admissible sets that are lever- aged by the PARG to ensure rollover prevention. Simulation results on a Fishhook maneuver show that the method robustly prevents rollover, and that the resulting parameter estimates are contained in the confidence sets produced by the Bayesian estimator. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CDC45484.2021.9683770 | 2021 60th IEEE Conference on Decision and Control (CDC) |
DocType | ISSN | ISBN |
Conference | 0743-1546 | 978-1-6654-3660-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karl Berntorp | 1 | 0 | 1.01 |
| Ankush Chakrabarty | 2 | 0 | 0.68 |
| Stefano Di Cairano | 3 | 0 | 1.01 |