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A Framework for Inference and Identification of Hybrid-System Models: Mixed Event-/Time-driven Systems (METS)

机译：混合系统模型的推理和识别框架：混合事件/时间驱动系统（METS）

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This paper proposes a simplified framework for the experimental inference and identification of models of hybrid systems. A problematic feature of such system identification is the presence of different “modes” of evolution of continuous state variables: this may necessitate not only the identification of the dynamics of the different modes, but also the identification of changes of mode. Inspired by the idea that the physics underlying the system is often invariant, this paper proposes a simplified framework that models hybrid systems in the form of separate untimed, “event-driven” and dynamical, “time-driven” components that are coupled only through input and output signals. Signals from the event-driven component are assumed to affect the dynamics of the time-driven component only in a relatively limited manner – either as direct inputs, or by modulating output feedback within the time-driven component; the “intrinsic,” “open-loop” dynamics of the time-driven component do not change. These assumptions largely decouple the estimation of the event- and time-driven components, avoiding the problem of distinguishing separate modes, and permitting the leveraging of standard system-identification methods. Two well known examples serve to illustrate the approach.
机译：本文为混合系统模型的实验推论和辨识提出了一个简化的框架。这种系统识别的一个有问题的特征是连续状态变量的演化存在不同的“模式”：这不仅需要识别不同模式的动力学，还需要识别模式的变化。受到系统底层物理通常不变的想法的启发，本文提出了一个简化的框架，该模型以单独的非定时，“事件驱动”和动态，“时间驱动”组件的形式对混合系统进行建模，这些组件仅通过输入和输出信号。假设事件驱动组件的信号仅以相对有限的方式影响时间驱动组件的动态，这些信号既可以直接输入，也可以通过在时间驱动组件内调制输出反馈来实现;时间驱动组件的“内在”，“开环”动态不会改变。这些假设在很大程度上消除了对事件和时间驱动组件的估计的耦合，避免了区分不同模式的问题，并允许利用标准系统识别方法。有两个众所周知的例子来说明这种方法。

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