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Structured controllers for uncertain systems: a stochastic optimization approach

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 te...

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Detalles Bibliográficos
Autor principal: Toscano, Rosario
Lenguaje:eng
Publicado: Springer 2013
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4471-5188-3
http://cds.cern.ch/record/1555604
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author Toscano, Rosario
author_facet Toscano, Rosario
author_sort Toscano, Rosario
collection CERN
description 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. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
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spelling cern-15556042021-04-21T22:37:16Zdoi:10.1007/978-1-4471-5188-3http://cds.cern.ch/record/1555604engToscano, RosarioStructured controllers for uncertain systems: a stochastic optimization approachEngineeringStructured 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. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.Springeroai:cds.cern.ch:15556042013
spellingShingle Engineering
Toscano, Rosario
Structured controllers for uncertain systems: a stochastic optimization approach
title Structured controllers for uncertain systems: a stochastic optimization approach
title_full Structured controllers for uncertain systems: a stochastic optimization approach
title_fullStr Structured controllers for uncertain systems: a stochastic optimization approach
title_full_unstemmed Structured controllers for uncertain systems: a stochastic optimization approach
title_short Structured controllers for uncertain systems: a stochastic optimization approach
title_sort structured controllers for uncertain systems: a stochastic optimization approach
topic Engineering
url https://dx.doi.org/10.1007/978-1-4471-5188-3
http://cds.cern.ch/record/1555604
work_keys_str_mv AT toscanorosario structuredcontrollersforuncertainsystemsastochasticoptimizationapproach