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Performance regulation of event-driven dynamical systems using infinitesimal perturbation analysis

机译:基于无穷微扰动分析的事件驱动动力系统的性能调节

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This paper presents a performance-regulation method for a class of stochastic timed event-driven systems aimed at output tracking of a given reference setpoint. The systems are either Discrete Event Dynamic Systems (DEDS) such as queueing networks or Petri nets, or Hybrid Systems (HS) with time-driven dynamics and event-driven dynamics, like fluid queues and hybrid Petri nets. The regulator, designed for simplicity and speed of computation, is comprised of a single integrator having a variable gain to ensure effective tracking under time-varying plants. The gain's computation is based on the Infinitesimal Perturbation Analysis (IPA) gradient of the plant function with respect to the control variable, and the resultant tracking can be quite robust with respect to modeling inaccuracies and gradient-estimation errors. The proposed technique is tested on examples taken from various application areas and modeled with different formalisms, including queueing models, Petri-net model of a production-inventory control system, and a stochastic DEDS model of a multicore chip control. Simulation results are presented in support of the proposed approach. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种针对一类随机定时事件驱动系统的性能调节方法,该系统旨在跟踪给定参考设定点的输出。这些系统可以是诸如排队网络或Petri网之类的离散事件动态系统(DEDS),也可以是具有时间驱动的动力学和事件驱动的动力学的混合系统(HS),例如流体队列和混合Petri网。为简化计算和设计速度而设计的调节器由具有可变增益的单个积分器组成,以确保在时变工厂下进行有效跟踪。增益的计算基于植物函数相对于控制变量的无穷微扰动分析(IPA)梯度,并且相对于建模误差和梯度估计误差,所得的跟踪结果可能非常健壮。所提出的技术在来自不同应用领域的示例上进行了测试,并以不同的形式进行建模,包括排队模型,生产库存控制系统的Petri-net模型以及多核芯片控制的随机DEDS模型。仿真结果被提出来支持所提出的方法。 (C)2016 Elsevier Ltd.保留所有权利。

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