Excitation-free closed-loop identification based on adaptive hysteresis loop width adjustment strategy

Abstract

Aiming at the problem that the traditional system identification methods are not adaptive enough when the system model parameters change significantly, this paper proposes an excitation-free closed-loop identification method based on an adaptive hysteresis loop width adjustment (AHLWA) strategy. Firstly, the AHLWA strategy is proposed according to the direction of change of the mean value of the power spectrum (MVPS) of the input signal, which can respond to the trend of the system's dynamic characteristics and dynamically adjust the hysteresis loop width parameters in real time. Secondly, an excitation-free closed-loop identification method based on the AHLWA strategy was developed by integrating the AHLWA strategy with the prediction error method. In addition, to accurately quantify the model error and detect model parameter variations, an improved model error detection method is proposed to quantify the model error by using the unexcited closed-loop identification technique. The numerical example simulation results indicate that the MVPS of the proposed identification method increases from 0.01 to 0.25 compared to the relay feedback identification method, which ensures the continuous excitation of the input signals and significantly improves the identification accuracy when the system model parameters change significantly. Meanwhile, the proposed identification method is further validated by applying it to the temperature control system of industrial coking furnaces. In addition, the proposed identification method can update the benchmark model on time, which makes the system model error significantly lower than 30%, providing an effective solution for model error detection in industrial closed-loop systems.