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Security of Cyber-Physical Systems: State Estimation and Control 2022 ed. [Kietas viršelis]

  • Formatas: Hardback, 277 pages, aukštis x plotis: 235x155 mm, weight: 623 g, 138 Illustrations, color; XXV, 277 p. 138 illus. in color., 1 Hardback
  • Serija: Studies in Systems, Decision and Control 396
  • Išleidimo metai: 20-Oct-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030883493
  • ISBN-13: 9783030883492
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 277 pages, aukštis x plotis: 235x155 mm, weight: 623 g, 138 Illustrations, color; XXV, 277 p. 138 illus. in color., 1 Hardback
  • Serija: Studies in Systems, Decision and Control 396
  • Išleidimo metai: 20-Oct-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030883493
  • ISBN-13: 9783030883492
Kitos knygos pagal šią temą:

This book analyzes the secure problems of cyber-physical systems from both the adversary and defender sides. Targeting the challenging security problems of cyber-physical systems under malicious attacks, this book presents some recent novel secure state estimation and control algorithms, in which moving target defense scheme, zero-sum game-theoretical approach, reinforcement learning, neural networks, and intelligent control are adopted. Readers will find not only the valuable secure state estimation and control schemes combined with the approaches aforementioned, but also some vital conclusions for securing cyber-physical systems, for example, the critical value of allowed attack probability, the maximum number of sensors to be attacked, etc. The book also provides practical applications, example of which are unmanned aerial vehicles, interruptible power system, and robot arm to validate the proposed secure algorithms. Given its scope, it offers a valuable resource for undergraduate and graduate students, academics, scientists, and engineers who are working in this field.

Introduction.- Optimal DoS Attack Scheduling for CPSs.- Active Defense
Control of CPSs via Sliding Mode.- Learning Tracking Control for CPSs.-
Intelligent Control for Nonlinear Networked Control Systems.- Reliable
Filtering of Sensor Networks.- Secure Estimation for CPSs via Sliding Mode.-
Zero-Sum Game Based Optimal Secure Control.- Proactive Secure Control for
CPSs. Fault-Tolerant Tracking Control for Nonstrict-Feedback Systems.- Deep
Reinforcement Learning Control Approach to Mitigating Attacks.- Conclusion
and Further Work.