Luigi Fortuna – författare

There are many books on advanced control for specialists, but not many present these topics for non-specialists. Assuming only a basic knowledge of automatic control and signals and systems, this second edition of Optimal and Robust Control offers a straightforward, self-contained handbook of advanced topics and tools in automatic control.

The book deals with advanced automatic control techniques, paying particular attention to robustness-the ability to guarantee stability in the presence of uncertainty. It explains advanced techniques for handling uncertainty and optimizing the control loop. It also details analytical strategies for obtaining reduced order models. The authors then propose using the Linear Matrix Inequality (LMI) technique as a unifying tool to solve many types of advanced control problems. Topics covered in the book include,

This easy-to-read text presents the essential theoretical background and provides numerous examples and MATLAB® exercises to help the reader efficiently acquire new skills. Written for electrical, electronic, computer science, space, and automation engineers interested in automatic control, this book can also be used for self-study of for a one-semester course in robust control.

This fully renewed second edition of the book also includes new fundamental topics such as Lyapunov functions for stability, variational calculus, formulation in terms of optimization problems of matrix algebraic equations, negative-imaginary systems, and time-delay systems.

There are many books on advanced control for specialists, but not many present these topics for non-specialists. Assuming only a basic knowledge of automatic control and signals and systems, this second edition of Optimal and Robust Control offers a straightforward, self-contained handbook of advanced topics and tools in automatic control.

The book deals with advanced automatic control techniques, paying particular attention to robustness-the ability to guarantee stability in the presence of uncertainty. It explains advanced techniques for handling uncertainty and optimizing the control loop. It also details analytical strategies for obtaining reduced order models. The authors then propose using the Linear Matrix Inequality (LMI) technique as a unifying tool to solve many types of advanced control problems. Topics covered in the book include,

This easy-to-read text presents the essential theoretical background and provides numerous examples and MATLAB® exercises to help the reader efficiently acquire new skills. Written for electrical, electronic, computer science, space, and automation engineers interested in automatic control, this book can also be used for self-study of for a one-semester course in robust control.

This fully renewed second edition of the book also includes new fundamental topics such as Lyapunov functions for stability, variational calculus, formulation in terms of optimization problems of matrix algebraic equations, negative-imaginary systems, and time-delay systems.

This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB®-based exercises to help readers effectively understand and apply the proposed methods. It offers a concise and accessible resource for learning automatic control, blending simplicity with clarity. Drawing on decades of teaching experience, the authors aim to provide an approachable introduction to the core concepts of the discipline, encouraging further exploration through independent study.

By establishing a strong foundation in these areas, the book prepares readers to tackle complex challenges in modern automatic control and excel in future academic and professional endeavors. Primarily intended for undergraduate engineering students, the book is also suitable for a wider audience. As automatic control is a foundational subject across numerous academic programs, this resource equips readers with essential analytical tools and introduces key problems, fostering deeper insights into the subject.

This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB®-based exercises to help readers effectively understand and apply the proposed methods. It offers a concise and accessible resource for learning automatic control, blending simplicity with clarity. Drawing on decades of teaching experience, the authors aim to provide an approachable introduction to the core concepts of the discipline, encouraging further exploration through independent study.

By establishing a strong foundation in these areas, the book prepares readers to tackle complex challenges in modern automatic control and excel in future academic and professional endeavors. Primarily intended for undergraduate engineering students, the book is also suitable for a wider audience. As automatic control is a foundational subject across numerous academic programs, this resource equips readers with essential analytical tools and introduces key problems, fostering deeper insights into the subject.

This book deals with nonlinear dynamics of electronic circuits, which could be used in robot control, secure communications, sensors and synchronized networks. The genesis of the content is related to a course on complex adaptive systems that has been held at the University of Catania since 2005. The efforts are devoted in order to emulate with nonlinear electronic circuits nonlinear dynamics. Step-by-step methods show the essential concepts of complex systems by using the Varela diagrams and accompanying MATLAB® exercises to reinforce new information. Special attention has been devoted to chaotic systems and networks of chaotic circuits by exploring the fundamentals, such as synchronization and control. The aim of the book is to give to readers a comprehensive view of the main concepts of nonlinear dynamics to help them better understand complex systems and their control through the use of electronics devices.

This book deals with nonlinear dynamics of electronic circuits, which could be used in robot control, secure communications, sensors and synchronized networks. The genesis of the content is related to a course on complex adaptive systems that has been held at the University of Catania since 2005. The efforts are devoted in order to emulate with nonlinear electronic circuits nonlinear dynamics. Step-by-step methods show the essential concepts of complex systems by using the Varela diagrams and accompanying MATLAB® exercises to reinforce new information. Special attention has been devoted to chaotic systems and networks of chaotic circuits by exploring the fundamentals, such as synchronization and control. The aim of the book is to give to readers a comprehensive view of the main concepts of nonlinear dynamics to help them better understand complex systems and their control through the use of electronics devices.

This brief provides a source of instruction from which students can be taught about the practicalities of designing and using chaotic circuits. The text provides information on suitable materials, circuit design and schemes for design realization. Readers are then shown how to reproduce experiments on chaos and to design new ones. The text guides the reader easily from the basic idea of chaos to the laboratory test providing an experimental basis that can be developed for such applications as secure communications.

This brief provides introductory information on sample chaotic circuits, includes coverage of their development, and the “gallery” section provides information on a wide range of circuits. Concise Guide to Chaotic Electronic Circuits will be useful to anyone running a laboratory class involving chaotic circuits and to students wishing to learn about them.

This brief is a clear, concise description of the main techniques of time series analysis —stationary, autocorrelation, mutual information, fractal and multifractal analysis, chaos analysis, etc.— as they are applied to the influence of wind speed and solar radiation on the production of electrical energy from these renewable sources. The problem of implementing prediction models is addressed by using the embedding-phase-space approach: a powerful technique for the modeling of complex systems. Readers are also guided in applying the main machine learning techniques for classification of the patterns hidden in their time series and so will be able to perform statistical analyses that are not possible by using conventional techniques.

The conceptual exposition avoids unnecessary mathematical details and focuses on concrete examples in order to ensure a better understanding of the proposed techniques.

This book addresses synchronization in networks of coupled systems. It illustrates the main aspects of the phenomenon through concise theoretical results and code, allowing readers to reproduce them and encouraging readers to pursue their own experimentation.

The book begins by introducing the mathematical representation of nonlinear circuits and the code for their simulation. This is followed by a brief account of the concept of the complex network, which describes the main aspects of complex networks and the main model types, with a particular focus on the code used to study and reproduce the models. 

The focus then shifts to the process through which independent nonlinear circuits that follow different trajectories without coupling share some properties of their motion: synchronization. The authors present the main techniques for studying synchronization in complex networks, including the major measures, the stability properties and control techniques. The book then moves on to advanced topics in synchronization of complex networks by examining forms of synchronization in which not all the units share the same trajectory, namely chimera states, clustering synchronization, and relay and remote synchronization. Simple codes for experimentation with these topics and control methods are also provided. In closing, the book addresses the problem of synchronization in time-varying networks.