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The authors review the different deterministic multi-objective optimization methods. In order to ameliorate the consequences of the computational expense typically involved in their use¿specifically the generation of multiple solutions among which the control engineer still has to choose¿algorithms for two-degree-of-freedom PID control are implemented in MATLAB®. MATLAB code and a MATLAB-compatible program are provided for download and will help readers to adapt the ideas presented in the text for use in their own systems. Further practical guidance is offered by the inclusion of several examples of common industrial processes amenable to the use of the authors¿ methods.
Researchers interested in non-heuristic approaches to controller tuning or in decision-making after a Pareto set has been established and graduate students interested in beginning a career working with PID control and/or industrial controller tuning will find this book a valuable reference and source of ideas.
The authors review the different deterministic multi-objective optimization methods. In order to ameliorate the consequences of the computational expense typically involved in their use¿specifically the generation of multiple solutions among which the control engineer still has to choose¿algorithms for two-degree-of-freedom PID control are implemented in MATLAB®. MATLAB code and a MATLAB-compatible program are provided for download and will help readers to adapt the ideas presented in the text for use in their own systems. Further practical guidance is offered by the inclusion of several examples of common industrial processes amenable to the use of the authors¿ methods.
Researchers interested in non-heuristic approaches to controller tuning or in decision-making after a Pareto set has been established and graduate students interested in beginning a career working with PID control and/or industrial controller tuning will find this book a valuable reference and source of ideas.
Orlando Arrieta received Bachelor's and Master's degrees in Electrical Engineering from the University of Costa Rica in 2003 and 2006 respectively. In 2007 he obtained a Master's degree in Systems Engineering and Automatic and in 2010 he received a Ph.D., both from the Autonomous University of Barcelona, ¿¿Spain, in thefield of PID Control. Between 2003 and 2005, he was an Interim Professor in the Automation Department of the School of Electrical Engineering of the University of Costa Rica. Later he became part of the research group in Advanced Control Systems of the Autonomous University of Barcelona, ¿¿where he also conducts a postdoctoral period. Since 2011, he is Professor of the Automation Department of the School of Electrical Engineering of the University of Costa Rica, reaching in 2015 the rank of Professor. He is a researcher at the Institute of Engineering Research (INII) and the Control Engineering Research Laboratory (CERLab). His research interests are focused on Process Control, applied to the PID Control. Since 2017 he is also Dean of the Faculty of Engineering.
Ramón Vilanova was born in Lérida, Spain, on September 10, 1968. He graduated in the Autonomous University of Barcelona (1991) obtaining the title of doctor through the same University (1996). At present he occupies the position of Lecturer at the School of Engineering of the Autonomous University of Barcelona where he develops educational tasks teaching subjects of Signals and Systems, Automatic Control and Technology of Automated Systems. His research interests include methods of tuning of PID regulators, systems with uncertainty, analysis of control systems with several degrees of freedom, application to environmental systems and development of methodologies for design of machine-man interfaces. He is author of several book chapters and has more than 100 publications in international congresses/journals. He is a member of IEEE and SIAM.
A good review of different scalarization methods helps the reader to solve multi-objective optimization problems
Provides the practitioner with examples of methods put into practice in common industrial processes
Readers can save time and effort with the associated MATLAB®-based application available for download with source code and database of optimal tunings
Includes supplementary material: [...]
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Nachrichtentechnik |
Genre: | Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Reihe: | Advances in Industrial Control |
Inhalt: |
xiv
148 S. 9 s/w Illustr. 85 farbige Illustr. 148 p. 94 illus. 85 illus. in color. |
ISBN-13: | 9783030723132 |
ISBN-10: | 3030723135 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Rojas, José David
Vilanova, Ramon Arrieta, Orlando |
Auflage: | 1st ed. 2021 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG Advances in Industrial Control |
Maße: | 235 x 155 x 10 mm |
Von/Mit: | José David Rojas (u. a.) |
Erscheinungsdatum: | 24.05.2022 |
Gewicht: | 0,26 kg |
Orlando Arrieta received Bachelor's and Master's degrees in Electrical Engineering from the University of Costa Rica in 2003 and 2006 respectively. In 2007 he obtained a Master's degree in Systems Engineering and Automatic and in 2010 he received a Ph.D., both from the Autonomous University of Barcelona, ¿¿Spain, in thefield of PID Control. Between 2003 and 2005, he was an Interim Professor in the Automation Department of the School of Electrical Engineering of the University of Costa Rica. Later he became part of the research group in Advanced Control Systems of the Autonomous University of Barcelona, ¿¿where he also conducts a postdoctoral period. Since 2011, he is Professor of the Automation Department of the School of Electrical Engineering of the University of Costa Rica, reaching in 2015 the rank of Professor. He is a researcher at the Institute of Engineering Research (INII) and the Control Engineering Research Laboratory (CERLab). His research interests are focused on Process Control, applied to the PID Control. Since 2017 he is also Dean of the Faculty of Engineering.
Ramón Vilanova was born in Lérida, Spain, on September 10, 1968. He graduated in the Autonomous University of Barcelona (1991) obtaining the title of doctor through the same University (1996). At present he occupies the position of Lecturer at the School of Engineering of the Autonomous University of Barcelona where he develops educational tasks teaching subjects of Signals and Systems, Automatic Control and Technology of Automated Systems. His research interests include methods of tuning of PID regulators, systems with uncertainty, analysis of control systems with several degrees of freedom, application to environmental systems and development of methodologies for design of machine-man interfaces. He is author of several book chapters and has more than 100 publications in international congresses/journals. He is a member of IEEE and SIAM.
A good review of different scalarization methods helps the reader to solve multi-objective optimization problems
Provides the practitioner with examples of methods put into practice in common industrial processes
Readers can save time and effort with the associated MATLAB®-based application available for download with source code and database of optimal tunings
Includes supplementary material: [...]
Erscheinungsjahr: | 2022 |
---|---|
Fachbereich: | Nachrichtentechnik |
Genre: | Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Reihe: | Advances in Industrial Control |
Inhalt: |
xiv
148 S. 9 s/w Illustr. 85 farbige Illustr. 148 p. 94 illus. 85 illus. in color. |
ISBN-13: | 9783030723132 |
ISBN-10: | 3030723135 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Rojas, José David
Vilanova, Ramon Arrieta, Orlando |
Auflage: | 1st ed. 2021 |
Hersteller: |
Springer International Publishing
Springer International Publishing AG Advances in Industrial Control |
Maße: | 235 x 155 x 10 mm |
Von/Mit: | José David Rojas (u. a.) |
Erscheinungsdatum: | 24.05.2022 |
Gewicht: | 0,26 kg |