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Controller tuning with evolutionary ...

Meza, Gilberto Reynoso.

Controller tuning with evolutionary multiobjective optimizationa holistic multiobjective optimization design procedure /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Controller tuning with evolutionary multiobjective optimizationby Gilberto Reynoso Meza ... [et al.].
Reminder of title:	a holistic multiobjective optimization design procedure /
other author:	Meza, Gilberto Reynoso.
Published:	Cham :Springer International Publishing :2017.
Description:	xiii, 227 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Multidisciplinary design optimization.
Online resource:	http://dx.doi.org/10.1007/978-3-319-41301-3
ISBN:	9783319413013$q(electronic bk.)

Controller tuning with evolutionary multiobjective optimizationa holistic multiobjective optimization design procedure /
Controller tuning with evolutionary multiobjective optimizationa holistic multiobjective optimization design procedure /[electronic resource] :by Gilberto Reynoso Meza ... [et al.]. - Cham :Springer International Publishing :2017. - xiii, 227 p. :ill., digital ;24 cm. - Intelligent systems, control and automation: science and engineering,v.852213-8986 ;. - Intelligent systems, control and automation: science and engineering ;v.70..

From the Contents: Part I Fundamentals -- Tutorial on Multiobjective Optimization Design procedure -- Review on MOOD procedure for controller tuning -- Tools for the MOOD procedure -- Part II Basics -- Controller tuning for SISO processes.

This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO) It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.

ISBN: 9783319413013$q(electronic bk.)

Standard No.: 10.1007/978-3-319-41301-3doiSubjects--Topical Terms:

257458
Multidisciplinary design optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.64

Controller tuning with evolutionary multiobjective optimizationa holistic multiobjective optimization design procedure /
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245 0 0 $a Controller tuning with evolutionary multiobjective optimization $h [electronic resource] : $b a holistic multiobjective optimization design procedure / $c by Gilberto Reynoso Meza ... [et al.].
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505 0 $a From the Contents: Part I Fundamentals -- Tutorial on Multiobjective Optimization Design procedure -- Review on MOOD procedure for controller tuning -- Tools for the MOOD procedure -- Part II Basics -- Controller tuning for SISO processes.
520 $a This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO) It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.
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