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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dk.um.si/IzpisGradiva.php?id=92310"><dc:title>Toward embedded system resources relaxation based on the event-triggered feedback control approach</dc:title><dc:creator>Sarjaš,	Andrej	(Avtor)
	</dc:creator><dc:creator>Gleich,	Dušan	(Avtor)
	</dc:creator><dc:subject>sliding mode control</dc:subject><dc:subject>event-triggered control</dc:subject><dc:subject>lowering computational intensity</dc:subject><dc:subject>task relaxation</dc:subject><dc:description>The paper describes an event-triggered nonlinear feedback controller design. Event triggering is a real-time controller implementation technique which reduces embedded system utilization
and relaxes task scheduling of the real-time system. In contrast to classic time implementation
techniques, the event-triggered execution is validated regarding the introduced triggering policy.
The triggering rule is a boundary, where the last task value is preserved until the rule is violated.
In the given paper, two different event-triggered strategies are designed for the class of dynamic
systems with integral behavior. Both methods are based on sliding mode controller design, where the
triggering rule of the first design involves only a partial state vector, which is a direct consequence of
the triggering rule derivation throughout the Lyapunov stability analysis. In the second approach,
the sliding mode controller is designed upon prior stabilized systems with the additional term, which
enables derivation of the triggering rule based on the whole state vector. The second approach offers
better closed-loop performance and higher relaxation of the system utilization. The selection of
triggering boundary is related closely to the derived minimal inter-event time, which impacts the
computational burden of the real-time system and closed-loop performance directly. The derived
controllers are compared with the classic sample and hold implementation techniques. The real-time
results are presented, and system performances are confirmed regarding embedded system task
relaxation, lowering the computational intensity and preserving closed-loop dynamics.</dc:description><dc:publisher>MDPI AG</dc:publisher><dc:date>2022</dc:date><dc:date>2025-03-28 12:12:18</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>92310</dc:identifier><dc:language>sl</dc:language><dc:rights>© 2022 by the authors</dc:rights></rdf:Description></rdf:RDF>
