Experimental evaluation of linear time-invariant models for feedback performance control in real-time systems

被引:0
作者
M. Amirijoo
J. Hansson
S. H. Son
S. Gunnarsson
机构
[1] Linköping University,Department of Computer and Information Science
[2] Carnegie Mellon University,Software Engineering Institute
[3] University of Virginia,Department of Computer Science
[4] Linköping University,Department of Electrical Engineering
来源
Real-Time Systems | 2007年 / 35卷
关键词
Feedback control scheduling; Modeling; Model validation; System identification;
D O I
暂无
中图分类号
学科分类号
摘要
In recent years a new class of soft real-time applications operating in unpredictable environments has emerged. Typical for these applications is that neither the resource requirements nor the arrival rates of service requests are known or available a priori. It has been shown that feedback control is very effective to support the specified performance of dynamic systems that are both resource insufficient and exhibit unpredictable workloads. To efficiently use feedback control scheduling it is necessary to have a model that adequately describes the behavior of the system. In this paper we experimentally evaluate the accuracy of four linear time-invariant models used in the design of feedback controllers. We introduce a model (DYN) that captures additional system dynamics, which a previously published model (STA) fails to include. The accuracy of the models are evaluated by validating the models with regard to measured data from the controlled system and through a set of experiments where we evaluate the performance of a set of feedback control schedulers tuned using these models. From our evaluations we conclude that second order models (e.g., DYN) are more accurate than first order models (e.g. STA). Further we show that controllers tuned using second order models perform better than controllers tuned using first order models.
引用
收藏
页码:209 / 238
页数:29
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