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A frequency domain step response identification method for continuous-time processes with time delay

机译:具有时间延迟的连续时间过程的频域阶跃响应识别方法

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摘要

Step response test is widely practiced for model identification in process industry. A frequency domain step response identification method is proposed for obtaining a continuous-time process model with time delay. By introducing a damping factor to the step response for realization of Laplace transform, a frequency response estimation algorithm is first proposed, in which only single integral is needed for computation, compared to recently developed identification methods based on multiple integral in time domain. Based on the estimated frequency response, two model fitting algorithms are developed analytically for obtaining a time delay model of first-, second-, or higher order with repetitive poles. Another two algorithms based on fitting multiple frequency response points thus estimated are proposed for obtaining a time delay model of any order, the latter of which may also be used to improve fitting accuracy over a specified frequency range interested to control design. Meanwhile, practical strategies to consolidate identification robustness against measurement noise are given based on consistent estimation analysis, together with a guideline for model structure selection to realize optimal fitting for identification of a high order process. Illustrative examples from recent references are used to demonstrate the effectiveness and merits of the proposed identification algorithms.
机译:阶跃响应测试在过程工业中广泛用于模型识别。提出了一种频域阶跃响应识别方法,用于获得具有时间延迟的连续时间过程模型。通过将阻尼因子引入阶跃响应中以实现拉普拉斯变换,首先提出了一种频率响应估计算法,与最近开发的基于时域多重积分的识别方法相比,该算法仅需要单个积分进行计算。基于估计的频率响应,分析性地开发了两种模型拟合算法,以获得具有重复极点的一阶,二阶或更高阶的时延模型。为了获得任何阶次的时延模型,提出了另外两种基于拟合由此估计的频率响应点的算法,该时延模型也可以用于提高控制设计感兴趣的指定频率范围内的拟合精度。同时,在一致的估计分析的基础上,给出了巩固识别对测量噪声的鲁棒性的实用策略,以及用于模型结构选择的准则,以实现对高阶过程的识别的最佳拟合。来自最新参考文献的说明性示例用于证明所提出的识别算法的有效性和优点。

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