Structured Controllers for Uncertain Systems : A Stochastic Optimization Approach

Rosario Toscano

ISBN 10: 1447159152 / ISBN 13: 9781447159155

Edité par Springer, Springer, 2015

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller). These strategies are based on a recently-developed stochastic optimization method termed the 'Heuristic Kalman Algorithm' (HKA) the use of which results in a simplified methodology that enables the solution of the structured control problem without a profusion of user-defined parameters. An overview of the main stochastic methods employable in the context of continuous non-convex optimization problems is also provided and various optimization criteria for the design of a structured controller are considered; H , H2, and mixed H2/H each merits a chapter to itself. Time-domain-performance specifications can be easily incorporated in the design.

N° de réf. du vendeur 9781447159155

Détails bibliographiques

• Titre: Structured Controllers for Uncertain Systems : A Stochastic Optimization Approach
• Éditeur: Springer, Springer
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 1447159152
• ISBN à 13 chiffres: 9781447159155
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 18 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 18 millimètres de profondeur
• Poids: 493 grammes

A propos de ce titre

Synopsis

Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller). These strategies are based on a recently-developed stochastic optimization method termed the "Heuristic Kalman Algorithm" (HKA) the use of which results in a simplified methodology that enables the solution of the structured control problem without a profusion of user-defined parameters. An overview of the main stochastic methods employable in the context of continuous non-convex optimization problems is also provided and various optimization criteria for the design of a structured controller are considered; H

∞, H2, and mixed H2/H∞ each merits a chapter to itself. Time-domain-performance specifications can be easily incorporated in the design.

À propos de l?auteur

Rosario Toscano was born in Catania, Italy. He received his masters degree with specialization in control from the Institut National des Sciences Appliquées de Lyon in 1996. He received the Ph.D. degree from the Ecole Centrale de Lyon in 2000. He received the HDR degree (Habilitation to Direct Research) from the University Jean Monnet of Saint-Etienne in 2007. He is currently an associate professor at the Ecole Nationale d'Ingénieurs de Saint-Etienne (ENISE). His research interests include dynamic reliability, fault detection, robust control, and multimodel approach applied to diagnosis and control.