Online control optimization using load driven scheduling

Lui Sha, Xue Liu, Marco Caccamo, Giorgio Buttazzo

Research output: Contribution to journalArticlepeer-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 languageEnglish (US)
Pages (from-to)4877-4882
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume5
DOIs
StatePublished - Dec 2000
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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