
Data-Driven Model-Free Controllers
CRC Press
1st Edition
Published on 27. December 2021
Book
Hardback
390 pages
978-0-367-69730-3 (ISBN)
Description
This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model-free and model-free adaptive-Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Academic and Professional Practice & Development
Illustrations
243 s/w Abbildungen, 1 s/w Photographie bzw. Rasterbild, 242 s/w Zeichnungen, 7 s/w Tabellen
7 Tables, black and white; 242 Line drawings, black and white; 1 Halftones, black and white; 243 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 26 mm
Weight
769 gr
ISBN-13
978-0-367-69730-3 (9780367697303)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Radu-Emil Precup | Raul-Cristian Roman | Ali Safaei
Data-Driven Model-Free Controllers
Book
01/2024
1st Edition
CRC Press
€77.30
Shipment within 15-20 days

Radu-Emil Precup | Raul-Cristian Roman | Ali Safaei
Data-Driven Model-Free Controllers
E-Book
12/2021
1st Edition
CRC Press
€69.99
Available for download

Radu-Emil Precup | Raul-Cristian Roman | Ali Safaei
Data-Driven Model-Free Controllers
E-Book
12/2021
1st Edition
CRC Press
€69.99
Available for download
Persons
Radu-Emil Precup is a Professor in the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
Raul-Cristian Roman is an Assistant Professor in the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
Ali Safaei is a postdoctoral researcher at Department of Mechanical Engineering, McGill University, Montreal, QC, Canada.
Raul-Cristian Roman is an Assistant Professor in the Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania.
Ali Safaei is a postdoctoral researcher at Department of Mechanical Engineering, McGill University, Montreal, QC, Canada.
Content
1. Introduction. 2. Iterative Feedback Tuning. 3. Intelligent PID Controllers. 4. Model-Free Sliding Mode Controllers. 5. Model-Free Adaptive Controllers. 6. Hybrid Model-Free and Model-Free Adaptive Virtual Reference Feedback Tuning controllers. 7. Hybrid model-free and model-free adaptive fuzzy controllers. 8. Cooperative Model-Free Adaptive Controllers for Multi-Agent Systems. Appendix 1. Simulation resutls for implementation of Model-Free Adaptive Controller on a differential-drive ground mobile robot.