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A State Event Detection Algorithm for Numerically Simulating Hybrid Systems with Model Singularities

机译:具有模型奇异性的混合系统数值模拟的状态事件检测算法

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This article describes an algorithm for detecting the occurrence of events, which signify discontinuities in the first derivative of the state variables, while simulating a set of nonsmooth differential equations. Such combined-discrete continuous systems arise in many contexts and are often referred to as hybrid systems, switched systems, or nonsmooth systems. In all cases, the state events are triggered at simulated times which generate states corresponding to the zeros of some algebraic "event" function. It has been noted that all existing simulators are prone to failure when these events occur in the neighborhood of model singularities—regions of the state space where the right-hand side of the differential equation is undefined. Such model singularities are often the impetus for using nonsmooth models in the first place. This failure occurs because existing algorithms blindly attempt to interpolate across singular regions, checking for possible events after the fact. The event detection algorithm described here overcomes this limitation using an approach inspired by feedback control theory. A carefully constructed extrapolation polynomial is used to select the integration step size by checking for potential future events, avoiding the need to evaluate the differential equation in potentially singular regions. It is shown that this alternate approach gives added functionality with little impact on the simulation efficiency.
机译:本文介绍了一种用于检测事件发生的算法,该算法表示状态变量的一阶导数中的不连续性,同时可以模拟一组非光滑的微分方程。这种组合离散连续系统出现在许多情况下,通常被称为混合系统,交换系统或非平滑系统。在所有情况下,状态事件都是在模拟时间触发的,该时间会生成与某些代数“事件”函数的零相对应的状态。已经注意到,当这些事件发生在模型奇点附近(状态空间中未定义微分方程右侧的区域)时,所有现有模拟器都容易发生故障。首先,这种模型奇异之处通常是使用不光滑模型的动力。之所以会发生这种故障,是因为现有算法盲目地尝试在单个区域内插值,然后检查可能的事件。此处描述的事件检测算法使用受反馈控制理论启发的方法克服了这一限制。通过仔细检查潜在的未来事件,可以使用精心构造的外推多项式来选择积分步长,从而无需评估潜在奇异区域中的微分方程。结果表明,这种替代方法提供的附加功能对仿真效率的影响很小。

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