Estimation and Inference in Discrete Event Systems
A Model-Based Approach with Finite Automata
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Beschreibung
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.
The book provides a systematic development of recursive algorithms for state estimation and event inference. The author also deals with the verification of pertinent properties such as:
the ability to determine the exact state of a system, “detectability”; the ability to ensure thatcertain classes of faults can be detected/identified, “diagnosability”; and the ability to ensure that certain internal state variables of the system remain “hidden” from the outside world regardless of the type of activity that is taking place, “opacity”. This book allows students, researchers and practicing engineers alike to grasp basic aspects of state estimation in discrete event systems, aspects like distributivity and probabilistic inference, quickly and without having to master the entire breadth of models that are available in the literature.
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.
The book provides a systematic development of recursive algorithms for state estimation and event inference. The author also deals with the verification of pertinent properties such as:
- the ability to determine the exact state of a system, “detectability”;
- the ability to ensure that certain classes of faults can be detected/identified, “diagnosability”; and
- the ability to ensure that certain internal state variables of the system remain “hidden” from the outside world regardless of the type of activity that is taking place, “opacity”.
Provides detailed discussion of opacity in discrete event systems and the verification of related privacy/security properties Readers gain more perspective for recursive algorithms for state estimation and event inference from the exercises and examples Drives a variety of problems of interest such as fault detection and identification
Autor*in
Christoforos N. Hadjicostis
Themen in »Estimation and Inference in Discrete Event Systems«
Discrete Event Systems State Estimation Formal Methods Fault Diagnosis and Verification of Diagnosability Opacity and Verification of Privacy Requirements Distributed/Decentralized State Estimation Distributed/Decentralized Fault Diagnosis