Nonlinear State Estimation with an Extended FMI 2.0 Co-Simulation Interface

Abstract

In this paper we propose a method how to automatically utilize continuous-time Modelica models directly in nonlinear state estimators. The approach is based on an extended FMI 2.0 Co-Simulation Interface [1] that interacts with the state estimation algorithms implemented in a Modelica library Besides a short introduction to Kalman Filter based state estimation, we give details on a generic interface to cooperate with FMUs in Modelica, an implementation of nonlinear state estimation based on this interface, and the Dymola prototype used for the evaluation. Finally we show first results in a tire load estimation application [3] for DLR's robotic electric research platform ROMO [4].