staging This is a test website.

Estimation and Inference in Discrete Event Systems A Model-Based Approach with Finite Automata

You must be logged in to access this title.

Sign up now

Already a member? Log in

Synopsis

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”; andthe 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.

Book details

Edition:
1st ed. 2020
Series:
Communications and Control Engineering
Author:
Christoforos N. Hadjicostis
ISBN:
9783030308216
Related ISBNs:
9783030308209
Publisher:
Springer International Publishing
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-10-17
Usage restrictions:
Copyright
Copyright date:
2020
Copyright by:
Springer Nature Switzerland AG 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Nonfiction, Science, Technology