State Space Modeling and Stable Dynamic Inversion for Trajectory Tracking on an Industrial Seat Test Rig

Abstract

This paper introduces a novel approach for trajectory tracking on seat test rigs. Seat test rigs are used in the automotive industry to test prototypes of new seats with respect to their comfort and vibration characteristics. Classically, a digital Fourier transform (DFT) approach, based on a Frequency Response Function (FRF) model, is used in this domain and different software packages exist that are based on this approach. The novel approach proposes state space models to identify the test rig and uses the recently developed Stable Dynamic Inversion (SDI) to invert the obtained state space models. The approach is validated on an industrial seat test rig and it is shown that the new approach is a competitive alternative to the existing DFT based methods. A closed loop experiment is also performed; this shows that the feedback controller allows one to reduce the state space model order without loss of accuracy.