Skip to main content
SpringerLink
Log in

Computational Intelligence and Optimization Methods for Control Engineering

  • Book
  • © 2019

Overview

Editors:
  1. Maude Josée Blondin

    1. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Panos M. Pardalos

    1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Javier Sanchis Sáez

    1. Institute of Automation and Industrial Computer, Polytechnic University of Valencia, Valencia, Spain

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Features case studies (Chapters 3-14) for engineering applications
  • Utilizes state-of-the-art in control optimization techniques
  • Provides the reader with future directions and insights into developing new techniques

Part of the book series: Springer Optimization and Its Applications (SOIA, volume 150)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 59.99 USD 109.00
45% discount Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 79.99 USD 139.99
43% discount Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 79.99 USD 139.99
43% discount Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (14 chapters)

  1. Front Matter

    Pages i-xv
    Download chapter PDF

  2. Control Engineering from Classical to Intelligent Control Theory—An Overview

    • Maude Josée Blondin, Javier Sanchis Sáez, Panos M. Pardalos
    Pages 1-30

  3. Main Metaheuristics Used for the Optimization of the Control of the Complex Systems

    • Pierre Borne, Amira Gharbi
    Pages 31-49

  4. Optimal Controller Parameter Tuning from Multi/Many-objective Optimization Algorithms

    • O. Tolga Altinoz
    Pages 51-74

  5. Fuzzy and Neuro-fuzzy Control for Smart Structures

    • Georgios K. Tairidis, Georgios E. Stavroulakis
    Pages 75-103

  6. Computational Intelligence in the Desalination Industry

    • Pedro Cabrera, José A. Carta
    Pages 105-131

  7. Control of Complex Biological Systems Utilizing the Neural Network Predictor

    • Samuel Oludare Bamgbose, Xiangfang Li, Lijun Qian
    Pages 133-148

  8. A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems

    • Azwirman Gusrialdi, Ying Xu, Zhihua Qu, Marwan A. Simaan
    Pages 149-172

  9. Distributed Optimization Based Control on the Example of Microgrids

    • Philipp Braun, Philipp Sauerteig, Karl Worthmann
    Pages 173-200

  10. Coherency Estimation in Power Systems: A Koopman Operator Approach

    • Harold R. Chamorro, Camilo A. Ordonez, Jimmy C.-H. Peng, Francisco Gonzalez-Longatt, Vijay K. Sood
    Pages 201-225

  11. Appliance Identification Through Nonintrusive Load Monitoring in Residences

    • Christos Gogos, George Georgiou
    Pages 227-244

  12. Management Suggestions for Process Control of Semiconductor Manufacturing: An Operations Research and Data Science Perspective

    • Marzieh Khakifirooz, Mahdi Fathi, Chen Fu Chien, Panos M. Pardalos
    Pages 245-274

  13. Feedback Control Algorithms for the Dissipation of Traffic Waves with Autonomous Vehicles

    • Maria Laura Delle Monache, Thibault Liard, Anaïs Rat, Raphael Stern, Rahul Bhadani, Benjamin Seibold et al.
    Pages 275-299

  14. Disturbance Rejection Run-to-Run Controller for Semiconductor Manufacturing

    • Marzieh Khakifirooz, Mahdi Fathi, Panos M. Pardalos
    Pages 301-319

  15. Energy Management Improvement Based on Fleet Digitalization Data Exploitation for Hybrid Electric Buses

    • Jon Ander López, Victor Isaac Herrera, Haritza Camblong, Aitor Milo, Haizea Gaztañaga
    Pages 321-355
Back to top

Keywords

About this book

This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader’s understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications.


Editors and Affiliations

  • Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, USA

    Maude Josée Blondin

  • Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

    Panos M. Pardalos

  • Institute of Automation and Industrial Computer, Polytechnic University of Valencia, Valencia, Spain

    Javier Sanchis Sáez

About the editors

Maude Blondin graduated with a PhD in Electrical Engineering from the Université du Québec à Trois-Rivières,  where she obtained the prestigious Vanier Canada Graduate Scholarship. During her PhD, she did a six-month internship at the Universidad Politecnica de Valencia, under the supervision of Javier Sanchis Saez. She moved to Florida to work in close collaboration with her PhD co-advisor, Panos M. Pardalos. Her doctoral research was on computational intelligence methods, and soft computing techniques applied to control engineering. Dr. Blondin is currently a postdoctoral researcher in the mechanical and aerospace engineering department at the University of Florida. She is expanding her research interests to the use of multiobjective optimization applied to multiagent control strategies. ​

Panos M. Pardalos serves as distinguished professor of industrial and systems engineering at the University of Florida. Additionally, he is the Paul andHeidi Brown Preeminent Professor of industrial and systems engineering. Pardalos is also an affiliated faculty member of the computer and information science department, the Hellenic Studies Center, and the biomedical engineering program. Additionally, he serves as the director of the Center for Applied Optimization. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing. Pardalos is a prolific author who lectures all over the world. He is the recipient of a multitude of fellowships and awards, the most recent of which is the Humboldt Research Award (2018).



Javier Sanchis Sáez received his B.Sc. (1993) and Ph.D. (2002) in Computer Science from Universidad Politécnica de Valencia (Spain). He is a professor in the Department of Systems Engineering and Control ofthe same university. His main research interests are multivariable predictive control, process optimisation and computational intelligence methods for control engineering. Professor Sanchis is co-author of Controller Tuning with Evolutionary Multiobjective Optimization (Springer, 2017) and is the author of more than fifty research papers on integration of computational intelligence methods with control engineering.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation