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|a 9789819930531
|9 978-981-99-3053-1
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|a 10.1007/978-981-99-3053-1
|2 doi
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|a Zhai, Chao.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Control and Optimization Methods for Complex System Resilience
|h [electronic resource] /
|c by Chao Zhai.
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| 250 |
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|a 1st ed. 2023.
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| 264 |
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1 |
|a Singapore :
|b Springer Nature Singapore :
|b Imprint: Springer,
|c 2023.
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| 300 |
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|a XX, 206 p. 68 illus., 62 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Studies in Systems, Decision and Control,
|x 2198-4190 ;
|v 478
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| 505 |
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|a Introduction to Complex System Resilience -- Optimal Control Approach to Identifying Cascading Failures -- Jacobian-free Newton-Krylov Method for Risk Identification -- Security Monitoring using Converse Lyapunov Function -- Online Gaussian Process Learning for Security Assessment -- Risk Identification of Cascading Process under Protection -- Model Predictive Approach to Preventing Cascading Process -- Robust Optimization Approach to Uncertain Cascading Process -- Cooperative Control Methods for Relieving System Stress -- Distributed Optimization Approach to System Protection -- Reinforcement Learning Approach to System Recovery -- Summary and Future Work.
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| 520 |
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|a This book provides a systematic framework to enhance the ability of complex dynamical systems in risk identification, security assessment, system protection, and recovery with the assistance of advanced control and optimization technologies. By treating external disturbances as control inputs, optimal control approach is employed to identify disruptive disturbances, and online security assessment is conducted with Gaussian process and converse Lyapunov function. Model predictive approach and distributed optimization strategy are adopted to protect the complex system against critical contingencies. Moreover, the reinforcement learning method ensures the efficient restoration of complex systems from severe disruptions. This book is meant to be read and studied by researchers and graduates. It offers unique insights and practical methodology into designing and analyzing complex dynamical systems for resilience elevation.
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|a Control engineering.
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| 650 |
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|a Robotics.
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|a Automation.
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| 650 |
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|a Cooperating objects (Computer systems).
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| 650 |
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|a Control, Robotics, Automation.
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| 650 |
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|a Cyber-Physical Systems.
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| 650 |
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|a Control and Systems Theory.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9789819930524
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| 776 |
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|i Printed edition:
|z 9789819930548
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| 776 |
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|i Printed edition:
|z 9789819930555
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| 830 |
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|a Studies in Systems, Decision and Control,
|x 2198-4190 ;
|v 478
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-99-3053-1
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| 912 |
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|a ZDB-2-INR
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| 912 |
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|a ZDB-2-SXIT
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| 950 |
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|a Intelligent Technologies and Robotics (SpringerNature-42732)
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| 950 |
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|a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)
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