Magdi S. Mahmoud – författare

Microgrids: Advanced Control Methods and Renewable Energy System Integration demonstrates the state-of-art of methods and applications of microgrid control, with eleven concise and comprehensive chapters. The first three chapters provide an overview of the control methods of microgrid systems that is followed by a review of distributed control and management strategies for the next generation microgrids. Next, the book identifies future research directions and discusses the hierarchical power sharing control in DC Microgrids.

Chapter 4 investigates the demand side management in microgrid control systems from various perspectives, followed by an outline of the operation and controls of the smart microgrids in Chapter 5. Chapter 6 deals with control of low-voltage microgrids with master/slave architecture.

The final chapters explain the load-Frequency Controllers for Distributed Power System Generation Units and the issue of robust control design for VSIs, followed by a communication solution denoted as power talk. Finally, in Chapter 11, real-time implementation of distributed control for an autonomous microgrid system is performed.

Advanced Control Design with Application to Electromechanical Systems represents the continuing effort in the pursuit of analytic theory and rigorous design for robust control methods. The book provides an overview of the feedback control systems and their associated definitions, with discussions on finite dimension vector spaces, mappings and convex analysis. In addition, a comprehensive treatment of continuous control system design is presented, along with an introduction to control design topics pertaining to discrete-time systems. Other sections introduces linear H1 and H2 theory, dissipativity analysis and synthesis, and a wide spectrum of models pertaining to electromechanical systems.

Finally, the book examines the theory and mathematical analysis of multiagent systems. Researchers on robust control theory and electromechanical systems and graduate students working on robust control will benefit greatly from this book.

Networked Control Systems: Cloud Control and Secure Control explores new technological developments in networked control systems (NCS), including new techniques, such as event-triggered, secure and cloud control. It provides the fundamentals and underlying issues of networked control systems under normal operating environments and under cyberphysical attack. The book includes a critical examination of the principles of cloud computing, cloud control systems design, the available techniques of secure control design to NCS's under cyberphysical attack, along with strategies for resilient and secure control of cyberphysical systems. Smart grid infrastructures are also discussed, providing diagnosis methods to analyze and counteract impacts.

Finally, a series of practical case studies are provided to cover a range of NCS's. This book is an essential resource for professionals and graduate students working in the fields of networked control systems, signal processing and distributed estimation.

New Trends in Observer-Based Control: A Practical Guide to Process and Engineering Applications presents a concise introduction to the latest advances in observer-based control design. The book gives a comprehensive tutorial on new trends in the design of observer-based controllers for which the separation principle is well established. It covers a wide range of applications, also including worked examples that make it ideal for both advanced courses and researchers starting work in the field. This book is also particularly suitable for engineers who want to quickly and efficiently enter the field.

New Trends in Observer-Based Control: An Introduction to Design Approaches and Engineering Applications, Volume One presents a clear-and-concise introduction to the latest advances in observer-based control design. It provides a comprehensive tutorial on new trends in the design of observer-based controllers for which the separation principle is well established. In addition, since the theoretical developments remain more advanced than the engineering applications, more experimental results are still needed. A wide range of applications are covered, and the book contains worked examples which make it ideal for both advanced courses and researchers starting in the field.

Cloud Control Systems: Analysis, Design and Estimation introduces readers to the basic definitions and various new developments in the growing field of cloud control systems (CCS). The book begins with an overview of cloud control systems (CCS) fundamentals, which will help beginners to better understand the depth and scope of the field. It then discusses current techniques and developments in CCS, including event-triggered cloud control, predictive cloud control, fault-tolerant and diagnosis cloud control, cloud estimation methods, and secure control/estimation under cyberattacks.

This book benefits all researchers including professors, postgraduate students and engineers who are interested in modern control theory, robust control, multi-agents control.

Advanced Distributed Consensus for Multiagent Systems contributes to the further development of advanced distributed consensus methods for different classes of multiagent methods. The book expands the field of coordinated multiagent dynamic systems, including discussions on swarms, multi-vehicle and swarm robotics. In addition, it addresses advanced distributed methods for the important topic of multiagent systems, with a goal of providing a high-level treatment of consensus to different versions while preserving systematic analysis of the material and providing an accounting to math development in a unified way. This book is suitable for graduate courses in electrical, mechanical and computer science departments.

Consensus control in multiagent systems is becoming increasingly popular among researchers due to its applicability in analyzing and designing coordination behaviors among agents in multiagent frameworks. Multiagent systems have been a fascinating subject amongst researchers as their practical applications span multiple fields ranging from robotics, control theory, systems biology, evolutionary biology, power systems, social and political systems to mention a few.

Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way.

The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints.

The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs.

In an uncertain and complex environment, to ensure secure and stable operations of large-scale power systems is one of the biggest challenges that power engineers have to address today. Traditionally, power system operations and decision-making in controls are based on power system computations of physical models describing the behavior of power systems. Largely, physical models are constructed according to some assumptions and simplifications, and such is the case with power system models. However, the complexity of power system stability problems, along with the system's inherent uncertainties and nonlinearities, can result in models that are impractical or inaccurate. This calls for adaptive or deep-learning algorithms to significantly improve current control schemes that solve decision and control problems.

Cyberphysical Infrastructures in Power Systems: Architectures and Vulnerabilities provides an extensive overview of CPS concepts and infrastructures in power systems with a focus on the current state-of-the-art research in this field. Detailed classifications are pursued highlighting existing solutions, problems, and developments in this area.

Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value.

It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.

Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value.

It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.