使用还原法优化振动系统的半主动阻尼

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED Advances in Computational Mathematics Pub Date : 2024-05-31 DOI:10.1007/s10444-024-10141-8
Jennifer Przybilla, Igor Pontes Duff, Peter Benner
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引用次数: 0

摘要

在本文中,我们考虑的是带有半主动阻尼的振动系统,该系统由二阶模型描述。为了最小化外部输入对系统响应的影响,我们对一些阻尼值进行了优化。作为最小化标准,我们评估能量响应,即系统相应传递函数的 \(\mathcal {H}_2\)-正态。计算能量响应包括求解不同阻尼参数的 Lyapunov 方程。因此,如果系统维度较大,最小化过程会导致较高的计算成本。我们提出了两种技术,通过对相应的参数 Lyapunov 方程应用还原基方法来减少优化问题。在第一种方法中,我们确定了一个缩小的求解空间,在此空间上可以在合理的时间内近似计算出 Lyapunov 方程以及由此产生的能量响应值。第二种方法包括最小化过程中的还原基础法。为了评估近似值的质量,我们引入了误差估算器来评估可控性格拉米安和能量响应的误差。最后,我们通过将这些方法应用于两个不同的例子来说明它们的优势。
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Semi-active damping optimization of vibrational systems using the reduced basis method

In this article, we consider vibrational systems with semi-active damping that are described by a second-order model. In order to minimize the influence of external inputs to the system response, we are optimizing some damping values. As minimization criterion, we evaluate the energy response, that is the \(\mathcal {H}_2\)-norm of the corresponding transfer function of the system. Computing the energy response includes solving Lyapunov equations for different damping parameters. Hence, the minimization process leads to high computational costs if the system is of large dimension. We present two techniques that reduce the optimization problem by applying the reduced basis method to the corresponding parametric Lyapunov equations. In the first method, we determine a reduced solution space on which the Lyapunov equations and hence the resulting energy response values are computed approximately in a reasonable time. The second method includes the reduced basis method in the minimization process. To evaluate the quality of the approximations, we introduce error estimators that evaluate the error in the controllability Gramians and the energy response. Finally, we illustrate the advantages of our methods by applying them to two different examples.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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