Abstract:

For high-order process objects with time-lag in industrial production, due to the complex structure of the controller, it is difficult to implement the method of directly designing the controller and reducing the order of the traditional model. In addition, noise will interfere with the controller. The above factors lead to unsatisfactory results using these methods. To solve these problems, the identification method based on step response is adopted in this study. By analyzing the input and output data of the step response of the object, a second-order plant with dead time model is established. The advantage of genetic algorithm to adapt the global search ability are used to optimize the static gain, time constant and pure hysteresis coefficient, so as to perform accurate model identification of high-order time-delay objects. MATLAB simulation results show that the proposed method has the advantages of high accuracy, strong robustness and wide applicability. Using this method to identify the model in the text under the unit step input signal, the ITAE indicators are 18.138 5, 6.271 5 and 167.889 2, respectively.

Key words: system identification, higher-order object, second-order plant with dead time model, MATLAB simulation, step response, genetic algorithm, model reduction, system optimization