RKH SPACE METHODS FOR LOW-LEVEL MONITORING AND CONTROL OF NONLINEAR-SYSTEMS .2. A VECTOR-CASE EXAMPLE - THE LORENZ SYSTEM

Authors
COVER A RENEKE J LENHART S PROTOPOPESCU V
Citation
A. Cover et al., RKH SPACE METHODS FOR LOW-LEVEL MONITORING AND CONTROL OF NONLINEAR-SYSTEMS .2. A VECTOR-CASE EXAMPLE - THE LORENZ SYSTEM, Mathematical models and methods in applied sciences, 7(6), 1997, pp. 823-845
Citations number
10
Categorie Soggetti
Mathematical Method, Physical Science",Mathematics
Journal title
Mathematical models and methods in applied sciences → ACNP
ISSN journal
02182025
Volume
7
Issue
6
Year of publication
1997
Pages
823 - 845
Database
ISI
SICI code
0218-2025(1997)7:6<823:RSMFLM>2.0.ZU;2-R
Abstract
By using techniques from the theory of reproducing kernel Hilbert (RKH ) spaces, we continue the exploration of the stochastic linearization method for possibly unknown and/or noise corrupted nonlinear systems. The aim of this paper is twofold: (a) the stochastic linearization for malism is explicitly extended to the vector case; and (b) as an illust ration, the performance of the stochastic linearization for monitoring and control is assessed in the case of the Lorenz system for which th e dynamic behavior is known independently.