Hybrid Estimation of Complex Systems

This monograph provides a tool-set for hybrid estimation that can successfully monitor the behavior of complex artifacts with a large number of possible operational and failure modes such as production plants, automotive or aeronautic systems, and autonomous robots. For this purpose, ideas from the...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Hofbaur, Michael W. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
Σειρά:Lecture Notes in Control and Information Science, 319
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Hofbaur, Michael W.  |e author. 
245 1 0 |a Hybrid Estimation of Complex Systems  |h [electronic resource] /  |c by Michael W. Hofbaur. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2005. 
300 |a XIX, 148 p. 69 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a Lecture Notes in Control and Information Science,  |x 0170-8643 ;  |v 319 
505 0 |a Hybrid Estimation at a Glance -- Probabilistic Hybrid Automata -- Hybrid Estimation -- Case Studies -- Conclusion. 
520 |a This monograph provides a tool-set for hybrid estimation that can successfully monitor the behavior of complex artifacts with a large number of possible operational and failure modes such as production plants, automotive or aeronautic systems, and autonomous robots. For this purpose, ideas from the fields of System Theory and Artificial Intelligence are taken and hybrid estimation is reformulated as a search problem. This allows to focus the estimation onto highly probably operational modes, without missing symptoms that might be hidden among the noise in the system. Additionally a novel approach to continue hybrid estimation in the presence of unknown behavioral modes and to automate system analysis and synthesis tasks for on-line operation are presented. This leads to a flexible model-based hybrid estimation scheme for complex artifacts that robustly copes with unforeseen situations. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
650 0 |a System theory. 
650 0 |a Vibration. 
650 0 |a Dynamical systems. 
650 0 |a Dynamics. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Mechatronics. 
650 1 4 |a Engineering. 
650 2 4 |a Control. 
650 2 4 |a Vibration, Dynamical Systems, Control. 
650 2 4 |a Applications of Mathematics. 
650 2 4 |a Control, Robotics, Mechatronics. 
650 2 4 |a Systems Theory, Control. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783540257271 
830 0 |a Lecture Notes in Control and Information Science,  |x 0170-8643 ;  |v 319 
856 4 0 |u http://dx.doi.org/10.1007/b105591  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)