ROBUST APPROXIMATE POLE ASSIGNMENT FOR 2ND-ORDER SYSTEMS - NEURAL-NETWORK COMPUTATION

Authors
Citation
Dwc. Ho et al., ROBUST APPROXIMATE POLE ASSIGNMENT FOR 2ND-ORDER SYSTEMS - NEURAL-NETWORK COMPUTATION, Journal of guidance, control, and dynamics, 21(6), 1998, pp. 923-929
Citations number
6
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Instument & Instrumentation","Aerospace Engineering & Tecnology
ISSN journal
0731-5090
Volume
21
Issue
6
Year of publication
1998
Pages
923 - 929
Database
ISI
SICI code
0731-5090(1998)21:6<923:RAPAF2>2.0.ZU;2-U
Abstract
A recurrent neural network approach to robust approximate pole assignm ent for second-order systems is proposed. The design is formulated as an unconstrained optimization problem and solved via the gradient-flow approach, which is ideally suited for neural network implementation. Convergence of the gradient flow also is established. Simulation resul ts are used to demonstrate the effectiveness of the proposed method.