Home > System Identification > 14th IFAC Symposium on System Identification, 2006 > State construction in subspace identification
State construction in subspace identification
System Identification, Volume # 14 | Part# 1
Location: , Australia
National Organizing Committee Chair: Brett Ninness,
Håkan Hjalmarsson
International Program Committee Chair: Iven Mareels
Conference Editor: Brett Ninness,
Håkan Hjalmarsson
Authors
Jan C. Willems; Ivan Markovsky; Bart De Moor
Identifier
10.3182/20060329-3-AU-2901.00043
Index Terms
most powerful unfalsified model,subspace identification,state construction
Abstract
In this presentation, we consider the problem of obtaining the state trajectory directly from an observed vector time-series. We show how the Hankel structure of the data matrix can be exploited in this construction. Both the cases of infinite as well as finite time-series are considered, but only deterministic systems are discussed.
References
[1] Markovsky, I., J. C. Willems and B. De Moor (2005).
Recursive computation of the most powerful unfalsified
model. Technical Report 05-169. Dept.
EE, K.U. Leuven.
[2] Rapisarda, P. and J. C. Willems (1997). State maps
for linear systems. SIAM J. Contr. Optim.
35(3), 1053-1091.
[3] Van Overschee, P. and B. De Moor (1994). N4SID:
subspace algorithms for the identification of
combined deterministic-stochastic systems. Automatica
30, 75-93.
[4] Van Overschee, P. and B. De Moor (1996). Subspace
Identification for Linear Systems: Theory, Implementation,
Applications. Kluwer.
[5] Willems, J. C. (1986, 1987). From time series to
linear system--Part I. Finite dimensional linear
time invariant systems, Part II. Exact modelling,
Part III. Approximate modelling. Automatica 22,
23, 561-580, 675-694, 87-115.
[6] Willems, J. C., P. Rapisarda, I. Markovsky and B. De
Moor (2005). A note on persistency of excitation.
Systems & Control Letters 54(4), 325-329.
