Verriest, Erik I. (Georgia Inst. of Tech.)

Uncertainty Equivalent Model Reduction

Scheduled for presentation during the Mini-Symposium "Dimension reduction of large-scale systems II" (ThP03), Thursday, July 27, 2006, 16:10−16:35, Room C2

17th International Symposium on Mathematical Theory of Networks and Systems, July 24-28, 2006, Kyoto, Japan

This information is tentative and subject to change. Compiled on May 19, 2024

Abstract

Model reduction via projection of dynamics (POD) of the balanced realization is revisited. The main concern is that POD leads to the deletion of information regarding the original system. This loss of information is equivalent to the introduction of uncertainty. Yet such uncertainty is typically not modelled in classical approaches to model reduction. In this paper we seek to quantify this uncertainty and provide realistic uncertainty bounds on the dynamics of the reduced order model, while not adding significantly to the computational complexity. The approach is based on a maximal likelihood estimate of the discarded state and stochastic system theory. It is shown that the original balanced realization provides enough information to specify such bounds. The problem is addressed also for the more recently introduced balancing for nonlinear systems.