Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data-Driven Model-Free Controllers PDF full book. Access full book title Data-Driven Model-Free Controllers by Radu-Emil Precup. Download full books in PDF and EPUB format.
Author: Radu-Emil Precup Publisher: CRC Press ISBN: 1000519635 Category : Technology & Engineering Languages : en Pages : 408
Book 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.
Author: Radu-Emil Precup Publisher: CRC Press ISBN: 1000519635 Category : Technology & Engineering Languages : en Pages : 408
Book 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.
Author: Zhongsheng Hou Publisher: CRC Press ISBN: 1466594187 Category : Technology & Engineering Languages : en Pages : 400
Book Description
Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
Author: Alexandre Sanfelice Bazanella Publisher: Springer Science & Business Media ISBN: 9400723008 Category : Technology & Engineering Languages : en Pages : 222
Book Description
Data-Based Controller Design presents a comprehensive analysis of data-based control design. It brings together the different data-based design methods that have been presented in the literature since the late 1990’s. To the best knowledge of the author, these data-based design methods have never been collected in a single text, analyzed in depth or compared to each other, and this severely limits their widespread application. In this book these methods will be presented under a common theoretical framework, which fits also a large family of adaptive control methods: the MRAC (Model Reference Adaptive Control) methods. This common theoretical framework has been developed and presented very recently. The book is primarily intended for PhD students and researchers - senior or junior - in control systems. It should serve as teaching material for data-based and adaptive control courses at the graduate level, as well as for reference material for PhD theses. It should also be useful for advanced engineers willing to apply data-based design. As a matter of fact, the concepts in this book are being used, under the author’s supervision, for developing new software products in a automation company. The book will present simulation examples along the text. Practical applications of the concepts and methodologies will be presented in a specific chapter.
Author: Steven L. Brunton Publisher: Cambridge University Press ISBN: 1009098489 Category : Computers Languages : en Pages : 615
Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Ali Khaki-Sedigh Publisher: John Wiley & Sons ISBN: 1394196407 Category : Science Languages : en Pages : 389
Book Description
An Introduction to Data-Driven Control Systems An introduction to the emerging dominant paradigm in control design Model-based approaches to control systems design have long dominated the control systems design methodologies. However, most models require substantial prior or assumed information regarding the plant’s structure and internal dynamics. The data-driven paradigm in control systems design, which has proliferated rapidly in recent decades, requires only observed input-output data from plants, making it more flexible and broadly applicable. An Introduction to Data-Driven Control Systems provides a foundational overview of data-driven control systems methodologies. It presents key concepts and theories in an accessible way, without the need for the complex mathematics typically associated with technical publications in the field, and raises the important issues involved in applying these approaches. The result is a highly readable introduction to what promises to become the dominant control systems design paradigm. Readers will also find: An overview of philosophical-historical issues accompanying the emergence of data-driven control systems Design analysis of several conventional data-driven control systems design methodologies Algorithms and simulation results, with numerous examples, to facilitate the implementation of methods An Introduction to Data-Driven Control Systems is ideal for students and researchers in control theory or any other research area related to plant design and production.
Author: Carlo Novara Publisher: Control, Robotics and Sensors ISBN: 1785617125 Category : Technology & Engineering Languages : en Pages : 300
Book Description
Using important examples, this book showcases the potential of the latest data-based and data-driven methodologies for filter and control design. It discusses the most important classes of dynamic systems, along with the statistical and set membership analysis and design frameworks.
Author: Ahmed Amine Jerraya Publisher: Springer Science & Business Media ISBN: 9401146985 Category : Computers Languages : en Pages : 441
Book Description
System-Level Synthesis deals with the concurrent design of electronic applications, including both hardware and software. The issue has become the bottleneck in the design of electronic systems, including both hardware and software, in several major industrial fields, including telecommunications, automotive and aerospace engineering. The major difficulty with the subject is that it demands contributions from several research fields, including system specification, system architecture, hardware design, and software design. Most existing book cover well only a few aspects of system-level synthesis. The present volume presents a comprehensive discussion of all the aspects of system-level synthesis. Each topic is covered by a contribution written by an international authority on the subject.
Author: J. Nathan Kutz Publisher: SIAM ISBN: 1611974496 Category : Science Languages : en Pages : 241
Book Description
Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Author: Radu-Emil Precup
Author: Radu-Emil Precup
Author: Zhongsheng Hou
Author: Alexandre Sanfelice Bazanella
Author: Steven L. Brunton
Author: Håkan Hjalmarsson
Author: Ali Khaki-Sedigh
Author: Carlo Novara
Author: David-Pieter Molenaar
Author: Ahmed Amine Jerraya
Author: J. Nathan Kutz