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Linear time-periodic dynamical systems: an H_2 analysis and a model reduction framework

机译:线性时间周期动力系统:H_2分析和模型归约框架

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Linear time-periodic (LTP) dynamical systems frequently appear in the modelling of phenomena related to fluid dynamics, electronic circuits and structural mechanics via linearization centred around known periodic orbits of nonlinear models. Such LTP systems can reach orders that make repeated simulation or other necessary analysis prohibitive, motivating the need for model reduction. We develop here an algorithmic framework for constructing reduced models that retains the LTP structure of the original LTP system. Our approach generalizes optimal approaches that have been established previously for linear time-invariant (LTI) model reduction problems. We employ an extension of the usual H-2 Hardy space defined for the LTI setting to time-periodic systems and within this broader framework develop an a posteriori error bound expressible in terms of related LTI systems. Optimization of this bound motivates our algorithm. We illustrate the success of our method on three numerical examples.
机译:线性时间周期(LTP)动力学系统经常通过以非线性模型的已知周期轨道为中心的线性化来出现在与流体动力学,电子电路和结构力学有关的现象的建模中。这样的LTP系统可能会达到禁止重复进行仿真或其他必要分析的订单,从而引发了对模型简化的需求。在这里,我们开发了一种算法框架,用于构建简化模型,该模型保留了原始LTP系统的LTP结构。我们的方法概括了先前针对线性时不变(LTI)模型简化问题建立的最佳方法。我们将为LTI设置定义的常规H-2 Hardy空间的扩展应用于时间周期系统,并在此更广泛的框架内开发出可以用相关LTI系统表示的后验误差界。此界限的优化激励了我们的算法。我们通过三个数值示例说明了我们方法的成功。

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