Introduction, Motivation and Geometric Tools

Abstract

In this Chapter, we summarize the main contributions of the book. In Section 1.1, we first give a short motivation for dealing with the multivariable system identification problem. In Section 1.2, we discuss in some more detail the main contributions which make that subspace identification algorithms are excellent tools to work with in an industrial environment. We also provide some historical background and compare our achievements to previously existing approaches to find black box mathematical models of systems. Notes on the organization of the book and a Chapter by Chapter overview can be found in Section 1.3. Finally, Section 1.4 introduces the main geometric and statistical tools, used for the development of, and the insights in subspace identification algorithms.

“The development of Subspace Methods is the most exciting thing that has happened to system identification the last 5 years or so…”

Professor Lennart Ljung from Linköping, Sweden at the second European Research Network System Identification workshop Louvain-la-Neuve, October 2, 1993.