Result: Design of Marx generators as a structured eigenvalue assignment

Title:
Design of Marx generators as a structured eigenvalue assignment
Source:
Automatica (Oxford). 50(10):2709-2717
Publisher Information:
Kidlington: Elsevier, 2014.
Publication Year:
2014
Physical Description:
print, 1/4 p
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Plans d'expériences, Experimental design, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Programmation mathématique, Mathematical programming, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Automatique théorique. Systèmes, Control theory. Systems, Synthèse des systèmes de commande, Control system synthesis, Electrotechnique. Electroenergetique, Electrical engineering. Electrical power engineering, Electroénergétique, Electrical power engineering, Réseaux et lignes électriques, Power networks and lines, Exploitation. Commande de charge. Fiabilité, Operation. Load control. Reliability, Assignation pôle, Pole assignment, Asignación polo, Base Gröbner, Gröbner basis, Calcul symbolique, Symbolic computation, Cálculo simbólico, Conception machine, Machine design, Concepción máquina, Géométrie algébrique, Algebraic geometry, Geometría algebraica, Identification système, System identification, Identificación sistema, Méthode polynomiale, Polynomial method, Método polinomial, Optimisation, Optimization, Optimización, Plan expérience, Experimental design, Plan experiencia, Programmation mathématique, Mathematical programming, Programación matemática, Programmation non convexe, Non convex programming, Programación no convexa, Réseau électrique, Electrical network, Red eléctrica, Synthèse commande, Control synthesis, Síntesis control, Design methodologies, Experiment design, Modeling operation and control of power systems, Optimization-based controller synthesis, Structured eigenvalue assignment
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Dipartimento di Ingegneria Civile e Ingegneria Informatica (DICII), Università di Roma Tor Vergata, Italy
CNRS, LAAS, 7 avenue du colonel Roche, 31400 Toulouse, France
Univ. de Toulouse, LAAS, 31400 Toulouse, France
Czech Technical University, Prague, Czech Republic
CNRS, IMB, Université de Bourgogne, 21078 Dijon, France
Wolfgang Pauli Institute, Vienna, Austria
Dipartimento di Ingegneria Industriale, University of Trento, Italy
ISSN:
0005-1098
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Electrical engineering. Electroenergetics

Mathematics

Operational research. Management
Accession Number:
edscal.28866935
Database:
PASCAL Archive

Further Information

We consider the design problem for a Marx generator electrical network, a pulsed power generator. We show that the components design can be conveniently cast as a structured real eigenvalue assignment with significantly lower dimension than the state size of the Marx circuit. Then we present two possible approaches to determine its solutions. A first symbolic approach consists in the use of Gröbner basis representations, which allows us to compute all the (finitely many) solutions. A second approach is based on convexification of a nonconvex optimization problem with polynomial constraints. We also comment on the conjecture that for any number of stages the problem has finitely many solutions, which is a necessary assumption for the proposed methods to converge. We regard the proof of this conjecture as an interesting challenge of general interest in the real algebraic geometry field.