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.
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 both adaptability and interpretability.
Preface. PART I: CPS FUNDAMENTALS AND NEW TRENDS. Fractional-Order
Distributed Parameter Systems for Smarter Cyber-Physical Systems: Challenges
and Opportunities. On Separation Between Learning and Control in Partially
Observed Markov Decision Processes. On the Impact of Sensor-Actuator Clock
Offsets on Off-Policy Reinforcement Learning. Decentralized Analysis and
Controller Synthesis of Networked Systems. Lyapunov Analysis for
Discrete-Time Stochastic Systems with Application to Network Consensus.
Event-Driven Distributed Cyber-Physical Systems. Digital Twins in CPS: The
State of the Art and Future Trends. PART II: CPS DESIGN AND CO-DESIGN
TECHNIQUES. Game-Theoretic Decision-Making for Autonomous Driving.
Cyber-Physical Systems for Human-Centric Automated Vehicles. Learning-Based
Control of Autonomous Vehicles in Mixed Vehicular Platoons. Robot Absolute
Positioning and Obstacle Avoidance: A Cyber-Physical System Approach.
Specification-Guided Safe Learning for Robotic Systems. On-Demand Emergency
Aerial Communication Using Directional Antennas: A CPS Co-design Approach.
PART III: SAFETY, RESILIENCE AND PRIVACY. Hybrid System-based Cyber-Attack
Identification and Mitigation. Online Identification of Adversarial Cognitive
Ability in Dynamic Games. Constructing Safety Certificates for Unknown Linear
H2 and H Control Problems. Scalable Attack-Resilient Algorithms for
Coordination in Networked Cyber-Physical Systems. Resilient Distributed
Learning in Multi-UAV Systems. Privacy-Aware Control of Cyber Physical
Systems. Index.
Yan Wan is a Distinguished University Professor in the Electrical Engineering Department at the University of Texas at Arlington (UTA). She is an Associate Fellow of AIAA and a Senior Member of IEEE.
Kyriakos G. Vamvoudakis currently serves as the Dutton-Ducoffe Endowed Professor at The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech. He is also a registered Electrical/Computer engineer (PE), a member of the Technical Chamber of Greece, an Associate Fellow of AIAA, and a Senior Member of IEEE.
Yangquan Chen had been a faculty of the School of Engineering, University of California, Merced (UCM) since 2012. He is listed in Highly Cited Researchers by Clarivate Analytics from 2018.
Frank L. Lewis is the Moncrief-O'Donnell Endowed Chair and a Professor of Electrical Engineering at The University of Texas at Arlington. He is a Fellow of National Academy of Inventors, a Life Fellow IEEE, Fellow IFAC, Fellow U.K. Inst. of Measurement and Control, Fellow AAAS.
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