𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Sampled-data model validation: An algorithm and experimental application

✍ Scribed by Geir Dullerud; Roy Smith

Publisher
John Wiley and Sons
Year
1996
Tongue
English
Weight
777 KB
Volume
6
Category
Article
ISSN
1049-8923

No coin nor oath required. For personal study only.

✦ Synopsis

The application of robust control theory requires representative models containing unknown bounded perturbations and unknown bounded noise/disturbance signals. Model validation is a means of assessing the applicability of a given model with respect to experimental data. We consider a sampled-data approach. using a continuollS time model. including unknown perturbations and signals, and a discrete experimental dablm of finite length. 1bc sampled-data model validation problem can be formulated as a linear matrix inequality problem. A computationally tractable algorithm, which employs data decimation and exploits the problem structure, is presented in the paper. This method is applied to a 2-D heating experiment.

πŸ“œ SIMILAR VOLUMES

Discrete-time frequency weighted model r
Discrete-time frequency weighted model reduction and application to sampled-data models
✍ Yoram Halevi; Natalya Raskin πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 145 KB πŸ‘ 1 views

The problem of frequency weighted optimal model order reduction for discrete-time systems is considered. Necessary conditions which completely characterize the reduced-order model are given. The solution of the problem consists of a set of one generalized Riccati equation and two generalized Lyapuno

A powerful new technique for the quantit
A powerful new technique for the quantitative validation of modeled and experimental data
✍ A. J. M. Williams; A. P. Duffy; M. S. Woolfson; T. M. Benson πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 114 KB πŸ‘ 2 views

A quantitati¨e ¨alidation procedure for comparisons of modeled and experimental data is described. This produces se¨eral le¨els of information, from a straightforward numerical assessment to detailed diagnostic data. Results show that this method has significant ad¨antages o¨er a ¨isual approach in