Fr. 86.00

Data-Driven Model-Free Controllers

Inglese · Tascabile

Spedizione di solito entro 1 a 3 settimane (non disponibile a breve termine)

Descrizione

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This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, and gives the in-depth theory and mathematical proofs behind them. Each chapter includes a section for presenting the theory and mathematical definitions as well as examples of the corresponding control algorithms.

Sommario

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.

Info autore

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.

Riassunto

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.

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