To provide an effective and personalised chest compression (CC) method for automatic mechanical compression devices, CC parameters must be improved according to the chest compression physiological feedback parameters (CCPFPs). The CCPFPs include the partial pressure of end-tidal CO2 and the mean arterial relaxation pressure. This study proposes a closed-loop controller for adjusting CCPFPs based on a fuzzy proportional integral derivative (PID) control algorithm. The performance of the fuzzy PID controller is evaluated and compared to that of a traditional PID controller in simulation studies based on a human circulation model. The simulation results demonstrate that the proposed fuzzy PID controller outperforms the traditional PID controller in CCPFPs regulation and maintenance. The fuzzy PID controller produces smoother CCPFPs regulation curves, shorter regulation time, fewer oscillations, smaller overshoot, and a significantly smaller peak depth than those of the traditional PID controller. The proposed closed-loop controller is thus potentially useful for practical cardiopulmonary resuscitation with its personalised and high-quality innovative automated control method for CC.