Kyriakos Vamvoudakis – författare

In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory�, "Adaptive Control and Neuroscience�, "Adaptive Learning Algorithms�, "Cyber-Physical Systems and Cooperative Control�, "Applications�.The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists.

This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems.

. Collection of chapters from several well-known professors and researchers that will showcase their recent work

. Presents different state-of-the-art control approaches and theory for complex systems

. Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams

. Real system examples and figures throughout, make ideas concrete

Includes chapters from several well-known professors and researchers that showcases their recent work Presents different state-of-the-art control approaches and theory for complex systems Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems

In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory, "Adaptive Control and Neuroscience, "Adaptive Learning Algorithms, "Cyber-Physical Systems and Cooperative Control, "Applications.The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists.This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems.• Collection of chapters from several well-known professors and researchers that will showcase their recent work• Presents different state-of-the-art control approaches and theory for complex systems• Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams• Real system examples and figures throughout, make ideas concrete- Includes chapters from several well-known professors and researchers that showcases their recent work- Presents different state-of-the-art control approaches and theory for complex systems- Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams- Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems

Control-Theoretic Methods for Cyber-Physical Security presents novel results on security and defense methodologies applied to cyber-physical systems. This book takes a control and game theory perspective, treating autonomous platforms as dynamic systems. It introduces algorithmic frameworks designed to proactively and reactively safeguard these systems against catastrophic failures. The algorithms showcased encompass a wide spectrum of security techniques, from model-free detection mechanisms to unpredictability-based defense strategies, combining both model-based and data-driven approaches.Serves as a bibliography on different aspects of security in cyber-physical systemsOffers insights into security through innovative approaches, which amalgamate principles from diverse disciplinesExplores unresolved challenges in the security domain, examining them through the lens of rigorous formulations from control and game theory

Control-theoretic Methods for Cyber-Physical Security presents novel results on security and defense methodologies applied to cyber-physical systems. This book adopts the viewpoint of control and game theories, modelling these autonomous platforms as dynamical systems and proposing algorithmic frameworks that both proactively and reactively shield the system against catastrophic failures. The algorithms presented employ model-based and data-driven techniques to security, ranging from model-free detection mechanisms to unpredictability-based defense approaches.This book will be a reference to the research community in identifying approaches to security that go beyond robustification techniques and give attention to the tight interplay between the physical and digital devices of the system, providing algorithms that can be readily used in a variety of application domains where the systems are subject to different kinds of attacks.- Serves as a bibliography on different aspects of security in cyber-physical systems- Offers insights into security through innovative approaches, which amalgamate principles from diverse disciplines- Explores unresolved challenges in the security domain, examining them through the lens of rigorous formulations from control and game theory

Cyber-Physical Systems (CPS) is featured by the tight integration of cyber and physical components. CPS has made major advances with a broad societal impact. Now in the era of Industry Revolution 4.0, CPS is considered as an enabling technology. Combined with autonomy, big data, machine learning and internet of things, CPS empowers systems with greater intelligence to address uncertainties, unknowns, attacks, and unexpected events.This book highlights the latest advances and explores the new trends in the design and implementation of smarter Cyber-Physical systems (CPS). It introduces integrated model-based and data-driven solutions for CPS that demonstrate features including both adaptability and interpretability. Key topics covered include reinforcement learning, digital twin and large-scale networks. The book then presents the latest codesign techniques that address practical computation, networking, control, and physical constraints. It examines important issues related to human CPS, safety, resilience and privacy. The chapters feature the tight integration of theory and practice, including problems motivated from applications, fundamental research development that are generally applicable, and implementation in real system applications. A wide range of CPS applications are covered, including robotics, autonomous driving, unmanned aerial vehicles and smart cities.

Cyber-Physical Systems (CPS) is featured by the tight integration of cyber and physical components. CPS has made major advances with a broad societal impact. Now in the era of Industry Revolution 4.0, CPS is considered as an enabling technology. Combined with autonomy, big data, machine learning and internet of things, CPS empowers systems with greater intelligence to address uncertainties, unknowns, attacks, and unexpected events.This book highlights the latest advances and explores the new trends in the design and implementation of smarter Cyber-Physical systems (CPS). It introduces integrated model-based and data-driven solutions for CPS that demonstrate features including both adaptability and interpretability. Key topics covered include reinforcement learning, digital twin and large-scale networks. The book then presents the latest codesign techniques that address practical computation, networking, control, and physical constraints. It examines important issues related to human CPS, safety, resilience and privacy. The chapters feature the tight integration of theory and practice, including problems motivated from applications, fundamental research development that are generally applicable, and implementation in real system applications. A wide range of CPS applications are covered, including robotics, autonomous driving, unmanned aerial vehicles and smart cities.