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Low-Order Control Design using a Reduced-Order Model with a Stability Constraint on the Full-Order Model

机译:使用在全阶模型上具有稳定性约束的降阶模型的低阶控制设计

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We propose a new algorithm for designing low-order controllers for large-scale linear time-invariant (LTI) dynamical systems with input and output. While the high cost of working with large-scale systems can mostly be avoided by first applying model order reduction, this can often result in controllers which fail to stabilize the closed-loop plant of the original full-order system. By considering a modified version of the optimal H∞ controller problem that incorporates both full- and reduced-order model data, our new method ensures stability while remaining efficient. Using a publicly available test set, we find that the controllers obtained by our method outperform those computed by RIFOO (H-Infinity Fixed-Order Optimization) when applied to reduced-order models alone.
机译:我们提出了一种新算法,用于设计具有输入和输出的大规模线性时不变(LTI)动力系统的低阶控制器。虽然通过首先应用模型阶数减少可以很大程度上避免使用大型系统的高成本,但这通常会导致控制器无法稳定原始全阶系统的闭环工厂。通过考虑结合了全阶和降阶模型数据的最优H∞控制器问题的改进版本,我们的新方法可确保稳定性,同时保持效率。使用公开可用的测试集,我们发现,仅将其应用于降阶模型时,通过我们的方法获得的控制器的性能要优于RIFOO(H-无穷大固定阶优化)所计算出的控制器。

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