๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Least-squares estimation of input/output models for distributed linear systems in the presence of noise

โœ Scribed by J.S. Gibson; G.H. Lee; C.-F. Wu

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
330 KB
Volume
36
Category
Article
ISSN
0005-1098

No coin nor oath required. For personal study only.

โœฆ Synopsis

This paper addresses least-squares estimation of parameters in digital input/output models of linear time-invariant distributed systems in the presence of white process and sensor noise. The systems of interest have state-space realizations in Hilbert spaces. Both "nite-dimensional and in"nite-dimensional input/output models are considered. The paper derives a number of new results for recursive least-squares estimation and "ltering. The main results characterize the asymptotic values to which parameter estimates converge with increasing amounts of data. The most important result is an equivalence between least-squares parameter estimation on an in"nite interval (i.e., with in"nitely long data sequences) and linear-quadratic optimal control on a "nite interval. Numerical results are presented for a sampled-data version of a wave equation.

๐Ÿ“œ SIMILAR VOLUMES

Unbiased parameter estimation of linear
Unbiased parameter estimation of linear systems in the presence of input and output noise
โœ Wei-Xing Zheng And; Chun-Bo Feng ๐Ÿ“‚ Article ๐Ÿ“… 1989 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 884 KB

It is well known that in practical situations the observed input-output data of an identified plant are usually corrupted by measurement noise. In this case the ordinary least-squares estimator of the system parameters is biased. In order to obtain a consistent estimator, a new type of modified leas

Output regulation for linear systems wit
Output regulation for linear systems with anti-stable eigenvalues in the presence of input saturation
โœ Raffaella De Santis ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 137 KB ๐Ÿ‘ 2 views

This paper studies the problem of output regulation for linear systems in the presence of input saturation in the full information case. It is assumed that the dynamic matrix has anti-stable eigenvalues and the class of disturbance and/or reference signals consists of constant, sinusoidal and zero m