Classical and Modern Optimization Techniques Applied to Control and Modeling
Language: English
Published by Taylor & Francis Ltd (Sales) Jun 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 160.42
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Add to basketItem description from seller
Neuware - The book presents a detailed and unified treatment of the theory and applications of optimization applied to control and modeling, focusing on nature-inspired optimization algorithms to optimally tune the parameters of linear and nonlinear controllers and models, with emphasis on tower crane systems and other representative applications.Classical and Modern Optimization Techniques Applied to Control and Modeling combines classical and modern approaches to optimization, based on the authors' experience in the field, and presents in a unified structure the essential aspects of optimization in control and modeling from a control engineer's point of view. It covers linear and nonlinear controllers, and neural networks based on reinforcement learning are considered and analyzed because of the need to reduce the complexity of the controllers and their design so that they can be practical to implement as low-cost automation solutions. The chapters are designed to quickly make the concepts of optimization, control, reinforcement learning, and neural networks understandable to readers with limited experience.This book is intended for a broad audience, including undergraduate and graduate students, engineers (designers, practitioners, and researchers), and anyone facing challenging control problems.…
Seller Inventory # 9781032785141
- Title
- Classical and Modern Optimization Techniques Applied to Control and Modeling
- Author
- Raul-Cristian Roman
- Publisher
- Taylor & Francis Ltd (Sales) Jun 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1032785144
- ISBN 13
- 9781032785141
- Item weight
- 508 grams
- Dimensions
- 234x156x19 mm
The book presents a detailed and unified treatment of the theory and applications of optimization applied to control and modeling, focusing on nature-inspired optimization algorithms to optimally tune the parameters of linear and nonlinear controllers and models, with emphasis on tower crane systems and other representative applications.
Classical and Modern Optimization Techniques Applied to Control and Modeling combines classical and modern approaches to optimization, based on the authors’ experience in the field, and presents in a unified structure the essential aspects of optimization in control and modeling from a control engineer’s point of view. It covers linear and nonlinear controllers, and neural networks based on reinforcement learning are considered and analyzed because of the need to reduce the complexity of the controllers and their design so that they can be practical to implement as low-cost automation solutions. The chapters are designed to quickly make the concepts of optimization, control, reinforcement learning, and neural networks understandable to readers with limited experience.
This book is intended for a broad audience, including undergraduate and graduate students, engineers (designers, practitioners, and researchers), and anyone facing challenging control problems.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Radu‐Emil Precup is a professor with the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania, and Senior Researcher (CS I) and the Head of the Data Science and Engineering Laboratory of the Center for Fundamental and Advanced Technical Research, Romanian Academy – Timisoara Branch, Romania.
Dr. Raul‐Cristian Roman is a lecturer with the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania. He received a PhD in systems engineering in 2018 from Politehnica University of Timisoara, Timisoara, Romania.
Dr. Elena-Lorena Hedrea is an assistant lecturer with the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
Dr. Alexandra-Iulia Szedlak-Stinean is a lecturer with the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
Iuliu Alexandru Zamfirache is a PhD student with the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
"About the title" may belong to another edition of this title.
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