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Multi-step-ahead Multivariate Predictors: A Comparative Analysis

Author

Summary, in English

The focus of this article is to undertake a comparative analysis of multi-step-ahead linear multivariate predictors. The approach considered for the estimation will be based on geometrically reliable linear algebra tools, resorting to subspace identification methods. A crucial issue is quantification of both bias error and variance affecting the estimate of the prediction for increasing values of the look ahead when only a small number of samples is available. No complete theory is available so far, nor sufficient numerical experience. Therefore, the analysis of this paper aims at shading some lights on the topic providing some insights and help to develop some intuitions.

Publishing year

2010

Language

English

Pages

2837-2842

Publication/Series

Proc. 49th IEEE Conf. Decision and Control (CDC2010)

Document type

Conference paper

Topic

  • Control Engineering

Conference name

49th IEEE Conference on Decision and Control

Conference date

2010-12-15

Conference place

Atlanta, Georgia, United States

Status

Published

Project

  • DIAdvisor

Research group

  • LCCC