利用管理中的自适应模糊控制

Mehmet H. Suzer, K. Kang
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引用次数: 12

摘要

越来越多的实时系统被嵌入到关键任务系统中,如目标跟踪系统,其中工作负载可能动态变化,例如,取决于感兴趣领域的目标数量。反馈控制已被应用于支持动态环境中的实时性能,产生了有希望的初步结果。然而,反馈控制所必需的数学系统建模是具有挑战性的。为了降低系统建模的难度,我们将模糊控制应用于利用误差(=目标利用率-当前利用率)与通过IF-THEN规则实现目标利用率所需的工作量调整之间的直接非线性映射。此外,通过在线自适应,我们的模糊控制器可以在必要时放大或减弱自己的模糊控制信号,以加快收敛到期望的利用率。在我们的模拟研究中,当工作负载发生显著变化时,我们的方法会迅速收敛到目标利用率。相反,测试基线在过载和未充分利用之间振荡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Fuzzy Control for Utilization Management
An increasing number of real-time systems are embedded in mission critical systems such as target tracking systems, in which workloads may dynamically vary, for example, depending on the number of targets in the area of interest Feedback control has been applied to support real-time performance in dynamic environments, producing promising initial results. However, mathematical system modeling necessary for feedback control is challenging. To reduce the difficulty of system modeling, we apply fuzzy control for direct nonlinear mappings between the utilization error (= target utilization - current utilization) and the workload adjustment required to achieve the target utilization via IF-THEN rules. Moreover, via online adaptation, our fuzzy controller can amplify or dampen its own fuzzy control signal, if necessary, to expedite the convergence to the desired utilization. In our simulation study, our approach quickly converges to the target utilization when the workload significantly changes. In contrast, the tested baselines oscillate between overload and underutilization.
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