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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	4877-4882
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	5
DOIs	https://doi.org/10.1109/CDC.2001.914703
State	Published - Dec 2000

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

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10.1109/CDC.2001.914703

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title = "Online control optimization using load driven scheduling",

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.",

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Online control optimization using load driven scheduling

Abstract

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