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Hybrid Estimation of Complex Systems

By: Hofbaur, Michael W [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Control and Information Science: 319Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.Description: XIX, 148 p. 69 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540315872.Subject(s): Engineering | Artificial intelligence | Applied mathematics | Engineering mathematics | System theory | Vibration | Dynamical systems | Dynamics | Control engineering | Robotics | Mechatronics | Engineering | Control | Vibration, Dynamical Systems, Control | Applications of Mathematics | Control, Robotics, Mechatronics | Systems Theory, Control | Artificial Intelligence (incl. Robotics)DDC classification: 629.8 Online resources: Click here to access online
Contents:
Hybrid Estimation at a Glance -- Probabilistic Hybrid Automata -- Hybrid Estimation -- Case Studies -- Conclusion.
In: Springer eBooksSummary: 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.
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E books E books PK Kelkar Library, IIT Kanpur
Available EBK7620
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Hybrid Estimation at a Glance -- Probabilistic Hybrid Automata -- Hybrid Estimation -- Case Studies -- Conclusion.

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.

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