The step response for hydraulic automatic gauge control (HAGC) determines the steel rolling speed and the steel sheet thickness in the process of rolling production. In this paper, the step response test process of HAGC was analysed, and a test approach was proposed for it. Based on that, the transfer function model of the step response test was established and simulated by using Matlab. In order to reduce the settling time and the overshoot, an adaptive proportional-integral-derivative (APID) link was presented in order to compensate for the input signal by using back propagation neural networks (BPNN). The experimental results show that the improved step response test model reaches the process requirements of HAGC, eliminates the jitter of the HAGC system at the start-up phase, and has better stability as well as faster response for steel sheet rolling. Keywords: step response, hydraulic automatic gauge control, proportional-integral-derived controller, artificial neural networks Highlights • Proposed the step response test model of HAGC system. • The working parameters study of the model. • Presented an APID link for signal compensation. • Representation of the stability and the flexibility on step response of the HAGC system.