Reduced-Order Observers for Nonlinear State Estimation in Flexible Multibody Systems

Abstract EN

Modern control schemes adopted in multibody systems take advantage of the knowledge of a large set of measurements of the most important state variables to improve system performances.

In the case of flexible-link multibody systems, however, the direct measurement of these state variables is not usually possible or convenient.

Hence, it is necessary to estimate them through accurate models and a reduced set of measurements ensuring observability.

In order to cope with the large dimension of models adopted for flexible multibody systems, this paper exploits model reduction for synthesizing reduced-order nonlinear state observers.

Model reduction is done through a modified Craig-Bampton strategy that handles effectively nonlinearities due to large displacements of the mechanism and through a wise selection of the most important coordinates to be retained in the model.

Starting from such a reduced nonlinear model, a nonlinear state observer is developed through the extended Kalman filter (EKF).

The method is applied to the numerical test case of a six-bar planar mechanism.

The smaller size of the model, compared with the original one, preserves accuracy of the estimates while reducing the computational effort.