Abstract: In actual industrial control systems, objects with non-minimum phases are a typical problem, especially when the zero point and time lag occur at the same time. This makes it difficult to achieve good results using conventional identification methods and an inability to meet industrial control requirements. To address this problem, we propose a new frequency-domain identification method that uses non-minimum phase process object models. Closed-loop control is simulated using Simulink in Matlab, and the input and the output signals generated in the simulation are decomposed and extracted. The Lass transform is used to analyze and obtain the frequency response characteristics of the process object in the important frequency range, and the least squares method is used to fit the amplitude and phase frequency parameters and accurately identify the object model. Compared with the traditional model identification method, the simulation experiment results show that the proposed identification method has good robustness and higher accuracy.