RLS-based online estimation on vehicle linear sideslip

This paper proposes an effective model-based approach to estimate vehicle linear sideslip online via recursive least square method (RLS) with forgetting. In this approach, a Luenberger observer is first designed to estimate vehicle states, including vehicle sideslip. Two lumped vehicle parameters in this observer are updated recursively to minimize the discrepancy between the model used and the physical plant and any possible effects caused by external unknown disturbances, in particular, road surface. Computer simulation and in-vehicle testing have been conducted to verify the proposed approach with results indicating that the proposed approach is very effective and robust in estimating vehicle linear sideslip under various road surfaces.