Online control optimization using load driven scheduling

Lui Sha; Xue Liu; Marco Caccamo; Giorgio Buttazzo

doi:10.1109/CDC.2001.914703

Online control optimization using load driven scheduling

Lui Sha
, Xue Liu
, Marco Caccamo
, Giorgio Buttazzo

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

30 Zitate (Scopus)

Abstract

In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.

Originalsprache	Englisch
Seiten (von - bis)	4877-4882
Seitenumfang	6
Fachzeitschrift	Proceedings of the IEEE Conference on Decision and Control
Jahrgang	5
DOIs	https://doi.org/10.1109/CDC.2001.914703
Publikationsstatus	Veröffentlicht - Dez. 2000
Extern publiziert	Ja

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10.1109/CDC.2001.914703

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abstract = "In many real-time control applications, the task periods are typically fixed and worst-case execution times are used in schedulability analysis. With the advancement of robotics, flexible visual sensing using cameras becomes a popular alternative to the use of embedded sensors. Unfortunately, the execution time of visual tracking varies greatly. In this paper, we integrate load driven online scheduling with direct digital designs to optimize control performance as a function of varying workload.",

author = "Lui Sha and Xue Liu and Marco Caccamo and Giorgio Buttazzo",

year = "2000",

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doi = "10.1109/CDC.2001.914703",

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M3 - Article

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JO - Proceedings of the IEEE Conference on Decision and Control

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Online control optimization using load driven scheduling

Abstract

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