Controller tuning with evolutionary multiobjective optimization : a holistic multiobjective optimization design procedure

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 i...

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Bibliographic Details
Main Author Meza, Gilberto Reynoso
Other Authors Blasco Ferragud, Xavier 1966-, Sanchis Saez, Javier, Herrero Durá, Juan Manuel
Format Electronic eBook
LanguageEnglish
Published Cham, Switzerland : Springer, [2017]
SeriesInternational series on intelligent systems, control and automation--science and engineering ; v. 85.
Subjects
Multidisciplinary design optimization.
Programmable controllers.
Evolutionary computation.
elektronické knihy
electronic books
Online AccessFull text
ISBN9783319413013
9783319412993
ISSN2213-8986 ;
Physical Description1 online resource

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100 1 |a Meza, Gilberto Reynoso. 
245 1 0 |a Controller tuning with evolutionary multiobjective optimization :  |b a holistic multiobjective optimization design procedure /  |c Gilberto Reynoso Meza, Xavier Blasco Ferragud, Javier Sanchis Saez, Juan Manuel Herrero Durá. 
260 |a Cham, Switzerland :  |b Springer,  |c [2017] 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Intelligent systems, control and automation: Science and engineering,  |x 2213-8986 ;  |v volume 85 
504 |a Includes bibliographical references. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
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. 
505 0 |a Preface; Acknowledgements; Contents; Acronyms; Part I Fundamentals; 1 Motivation: Multiobjective Thinking in Controller Tuning; 1.1 Controller Tuning as a Multiobjective Optimization Problem: A Simple Example; 1.2 Conclusions on This Chapter; References; 2 Background on Multiobjective Optimization for Controller Tuning; 2.1 Definitions; 2.2 Multiobjective Optimization Design (MOOD) Procedure; 2.2.1 Multiobjective Problem (MOP) Definition; 2.2.2 Evolutionary Multiobjective Optimization (EMO); 2.2.3 MultiCriteria Decision Making (MCDM); 2.3 Related Work in Controller Tuning. 
505 8 |a 2.3.1 Basic Design Objectives in Frequency Domain2.3.2 Basic Design Objectives in Time Domain; 2.3.3 PI-PID Controller Design Concept; 2.3.4 Fuzzy Controller Design Concept; 2.3.5 State Space Feedback Controller Design Concept; 2.3.6 Predictive Control Design Concept; 2.4 Conclusions on This Chapter; References; 3 Tools for the Multiobjective Optimization Design Procedure; 3.1 EMO Process; 3.1.1 Evolutionary Technique; 3.1.2 A MOEA with Convergence Capabilities: MODE; 3.1.3 An MODE with Diversity Features: sp-MODE; 3.1.4 An sp-MODE with Pertinency Features: sp-MODE-II; 3.2 MCDM Stage. 
505 8 |a 3.2.1 Preferences in MCDM Stage Using Utility Functions3.2.2 Level Diagrams for Pareto Front Analysis; 3.2.3 Level Diagrams for Design Concepts Comparison ; 3.3 Conclusions of This Chapter; References; Part II Basics; 4 Controller Tuning for Univariable Processes; 4.1 Introduction; 4.2 Model Description; 4.3 The MOOD Approach; 4.4 Performance of Some Available Tuning Rules; 4.5 Conclusions; References; 5 Controller Tuning for Multivariable Processes; 5.1 Introduction; 5.2 Model Description and Control Problem; 5.3 The MOOD Approach; 5.4 Control Tests; 5.5 Conclusions; References. 
505 8 |a 6 Comparing Control Structures from a Multiobjective Perspective6.1 Introduction; 6.2 Model and Controllers Description; 6.3 The MOOD Approach; 6.3.1 Two Objectives Approach; 6.3.2 Three Objectives Approach; 6.4 Conclusions; References; Part III Benchmarking; 7 The ACC'1990 Control Benchmark: A Two-Mass-Spring System; 7.1 Introduction; 7.2 Benchmark Setup: ACC Control Problem; 7.3 The MOOD Approach; 7.4 Control Tests; 7.5 Conclusions; References; 8 The ABB'2008 Control Benchmark: A Flexible Manipulator; 8.1 Introduction; 8.2 Benchmark Setup: The ABB Control Problem; 8.3 The MOOD Approach. 
505 8 |a 8.4 Control Tests8.5 Conclusions; References; 9 The 2012 IFAC Control Benchmark: An Industrial Boiler Process; 9.1 Introduction; 9.2 Benchmark Setup: Boiler Control Problem; 9.3 The MOOD Approach; 9.4 Control Tests; 9.5 Conclusions; References; Part IV Applications; 10 Multiobjective Optimization Design Procedure for Controller Tuning of a Peltier Cell Process; 10.1 Introduction; 10.2 Process Description; 10.3 The MOOD Approach; 10.4 Control Tests; 10.5 Conclusions; References; 11 Multiobjective Optimization Design Procedure for Controller Tuning of a TRMS Process; 11.1 Introduction. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Multidisciplinary design optimization. 
650 0 |a Programmable controllers. 
650 0 |a Evolutionary computation. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
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700 1 |a Blasco Ferragud, Xavier  |q (Francesc Xavier),  |d 1966- 
700 1 |a Sanchis Saez, Javier. 
700 1 |a Herrero Durá, Juan Manuel. 
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830 0 |a International series on intelligent systems, control and automation--science and engineering ;  |v v. 85. 
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