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Estimation and Inference in Discrete Event Systems chooses a popular model for emerging automation systems—finite automata under partial observation—and focuses on a comprehensive study of the key problems of state estimation and event inference. The text includes treatment of current, delayed, and initial state estimation. Related applications for assessing and enforcing resiliency—fault detection and diagnosis—and security—privacy and opacity—properties are discussed, enabling the reader to apply these techniques in a variety of emerging applications, among them automated manufacturing processes, intelligent vehicle/highway systems, and autonomous vehicles.
Introduction to Estimation and Inference in Discrete Event Systems.
Preliminaries and Notation.
Finite Automata Models.
State Estimation.
Verification of State Isolation Properties.
Detectability.
Diagnosability.
Opacity.
Decentralized State Estimation.
Distributed State Estimation