Structured Controllers for Uncertain Systems (eBook)

A Stochastic Optimization Approach
eBook Download: PDF
2013 | 2013
XXIV, 298 Seiten
Springer London (Verlag)
978-1-4471-5188-3 (ISBN)

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Structured Controllers for Uncertain Systems -  Rosario Toscano
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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.

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.


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 "e;Heuristic Kalman Algorithm"e; (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; Hinfinity, H2, and mixed H2/Hinfinity each merits a chapter to itself. Time-domain-performance specifications can be easily incorporated in the design.

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.

Standard Stochastic Optimisation Methods.- Heuristic Kalman Algorithm.- Uncertain Linear Systems and Robustness.- H∞ Design of Fixed Structure Controllers.- H2 Design of Fixed Structure Controllers.- Mixed H2/H∞ Design of Fixed Structure Controllers.- Extension to Nonlinear Control via Multimodel Approach.

Erscheint lt. Verlag 29.5.2013
Reihe/Serie Advances in Industrial Control
Zusatzinfo XXIV, 298 p.
Verlagsort London
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Analysis
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Schlagworte Constrained Control • Control Applications • Heuristic Kalman Algorithm • Low-order Control • Robust Control • stochastic optimization • Structured Control • Uncertain systems
ISBN-10 1-4471-5188-7 / 1447151887
ISBN-13 978-1-4471-5188-3 / 9781447151883
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