Detection of different type events in hybrid dynamical systems

E. Popov, Y. Shornikov
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Abstract

Hybrid dynamical or simply hybrid systems (HS) are a modern apparatus for modeling discrete-continuous processes in different applications such as power engineering, aeronautics, manufacturing, economics, transport dispatching, etc. The key difference of HSs from classical dynamic systems is the presence of continuous mode switching events. Event times are defined by the zeroes of continuous event functions. If it is impossible to symbolically compute an event time. To do it one uses an event detection algorithm working together with a differential equation integration algorithm. Events in HSs are traditionally divided into state events and time events. Only explicit time events with event functions in the form of linear polynomials in time are usually considered in the literature. This paper addresses the class of implicit time events and lists their possible sources. Moreover, the traditional classification of events into unilateral, bilateral and accuracy critical events is expanded by adding difficult-to-detect events. These events are characterized by event functions crossing zero several times within one integration step. Not all algorithms can guarantee detecting events of this type. Heterogeneous HSs including processes of different physical nature are in general characterized by significantly stiff and high-dimensional modes usually defined in a form of differential-algebraic systems of equations with events of different types. The last feature limits the application of classical event detection algorithms oriented to a single event type. That is why the paper proposes the methodology of complex event detection consisting in using separate event detection algorithm for each event type. The joint work of several algorithms can ensure correct detection of events of different types and also may improve the efficiency. A complex event detection algorithm guaranteeing detection of all events is constructed for a particular HS. The complex algorithm demonstrates an average speed up of 17%.
混合动力系统中不同类型事件的检测
混合动力系统或简称混合系统(HS)是一种现代设备,用于模拟不同应用中的离散连续过程,如电力工程、航空、制造、经济、运输调度等。高速系统与经典动态系统的主要区别在于存在连续的模式切换事件。事件时间由连续事件函数的零点定义。如果不可能用符号来计算事件时间。要做到这一点,需要使用事件检测算法和微分方程积分算法一起工作。HSs中的事件通常分为状态事件和时间事件。文献中通常只考虑事件函数为时间线性多项式形式的显式时间事件。本文讨论了一类隐式时间事件,并列出了它们的可能来源。此外,通过添加难以检测的事件,将传统的事件分类扩展为单侧、双边和准确性关键事件。这些事件的特征是事件函数在一个积分步骤内多次越过零。并不是所有的算法都能保证检测到这种类型的事件。包括不同物理性质的过程在内的异质hs通常具有明显的刚性和高维模式,通常以具有不同类型事件的微分代数方程组的形式定义。最后一个特性限制了面向单一事件类型的经典事件检测算法的应用。因此,本文提出了复杂事件检测方法,即对每种事件类型使用单独的事件检测算法。多种算法的协同工作可以保证对不同类型事件的正确检测,也可以提高效率。针对特定HS,构造了一种复杂事件检测算法,保证对所有事件进行检测。该复杂算法的平均速度提高了17%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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