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Control Theory of Digitally Networked Dynamic Systems electronic resource edited by Jan Lunze.

Contributor(s): Lunze, Jan [editor.] | SpringerLink (Online service)Material type: TextTextPublication details: Heidelberg : Springer International Publishing : Imprint: Springer, 2014Description: XVIII, 394 p. 136 illus., 3 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319011318Subject(s): engineering | Systems theory | Engineering | control | Systems Theory, ControlDDC classification: 629.8 LOC classification: TJ212-225Online resources: Click here to access online
Contents:
Introduction to networked control systems -- Analysis of networked systems -- Distributed estimation and control -- Distributed and networked model predictive control -- Event-based control -- Multi-agent systems -- Wireless networking for control.
In: Springer eBooksSummary: The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.  .
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Introduction to networked control systems -- Analysis of networked systems -- Distributed estimation and control -- Distributed and networked model predictive control -- Event-based control -- Multi-agent systems -- Wireless networking for control.

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.  .

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