Abstract

In this paper, a simple yet robust closed-loop identification method based on step response is presented. By approximating the process response firstly using Laguerre series expansions, a high-order process transfer function can be obtained. Then, a linear two-step reduction technique is used to reduce the high-order process to a second-order plus time delay model based on the frequency response data. This method is robust to measurement noise and it also does not need any numerical technique or iterative optimization. Simulation examples show the effectiveness of the proposed method for different process models. Comparison of identification performance between different methods is also illustrated in this work.

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