Vehicle Rollover Index Estimation Using a Nonlinear Unknown Input Observer.

This paper proposes an LMI-based nonlinear unknown input observer to estimate the rollover index of the autonomous vehicle, whether the rollover is tripped or untripped. To tackle the rollover prevention-related model, some transformations are introduced with the goal to satisfy specific necessary rank conditions and to simplify the structure of the nonlinear model. In addition, to propose a more general method, the L-2-optimality criterion is considered in order to get an estimation with H-infinity performance with respect to system disturbances and measurement noises. After presenting the generic numerical design procedure, simulations using Matlab/Simulink and CarSim are provided. The results obtained from CarSim simulations show that the developed nonlinear observer reliably estimates the vehicle states, the unknown normal tire forces, and the rollover index to predict tripped and untripped rollovers.