Parameter Identification Method Based on Repetitive and Non-repetitive Pole Plus Delay Model

System identification methods are generally divided into non-parametric identification and parameter identification. This study introduces a new parameter identification method. Two transfer function models are used to fit the controlled object, and the Laplacian form of transfer function in frequency domain is obtained. On this basis, only two differential treatments are required to obtain the integral formula of parameters. Simulink in MATLAB is used to obtain the input and output data of the step response of the controlled object under open and closed control systems. The appropriate damping factor is introduced into the Laplace formula. Then, the transfer function and its primary and secondary differential formulas are calculated using the trapezoidal integral algorithm in MATLAB. When the transfer function model adopts the multiple poles plus time-delay model, the model has only two unknown parameters, which can be calculated directly based on the transfer function and its first and second differential formulas. When the transfer function adopts the second-order plus time-delay model, the model has three unknown parameters. This study adopts a minimization error-least square method to calculate the parameters. Finally, six types of simulation controlled objects are provided. Three of them are identified by two identification models compared with the identification methods in recent years. The Nyquist diagram and the output error value of the model and identification model are obtained through MATLAB simulation. Results show that the identification method in this study is simple and effective, and it has the advantages of small calculation, high identification accuracy, and good robustness.