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Optimization-based design of plant-friendly multisine signals using geometric discrepancy criteria

机译：基于几何差异准则的基于优化的植物友好型多正弦信号设计

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摘要

System identification is an important means for obtaining dynamical models for process control applications; experimental testing represents the most time-consuming step in this task. The design of constrained, '' plant-friendly '' multisine input signals that optimize a geometric discrepancy criterion arising from Weyl's Theorem is examined in this paper. Such signals are meaningful for data-centric estimation methods, where uniform coverage of the output state-space is critical. The usefulness of this problem formulation is demonstrated by applying it to a linear problem example and to the nonlinear, highly interactive distillation column model developed by Weischedel and McAvoy. The optimization problem includes a search for both the Fourier coefficients and phases in the multisine signal, resulting in an uniformly distributed output signal displaying a desirable balance between high and low gain directions. The solution involves very little user intervention (which enhances its practical usefulness) and has great benefits compared to multisine signals that minimize crest factor. The constrained nonlinear optimization problems that are solved represent challenges even for high-performance optimization software.
机译：系统识别是获取过程控制应用动力学模型的重要手段。实验测试是此任务中最耗时的步骤。本文研究了约束的，“植物友好的”多正弦输入信号的设计，该信号优化了由韦尔定理引起的几何差异准则。这样的信号对于以数据为中心的估计方法很有意义，在这些方法中，输出状态空间的均匀覆盖至关重要。通过将其应用于线性问题示例以及由Weischedel和McAvoy开发的非线性，高度交互的蒸馏塔模型，可以证明此问题公式的有用性。优化问题包括在多正弦信号中搜索傅立叶系数和相位，从而导致输出信号均匀分布，从而在高增益和低增益方向之间显示出理想的平衡。与多正弦信号相比，该解决方案几乎不需要用户干预（从而增强了其实用性），并且具有极大的优势，可将波峰因数最小化。即使对于高性能优化软件，所解决的受约束的非线性优化问题也构成了挑战。

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