In order to solve the problems of boundary mutation, poor stability and difficult determination of modal parameters in mode conversion of shearer mining height control system based on human-simulated intelligent control, a human-simulated intelligent control model based on fuzzy logic to improve mode switching and particle swarm optimization to optimize parameters is proposed. The model extends the characteristic mode of the human-simulated intelligent control error phase plane to a fuzzy set. The optimal control mode is selected in real time by fuzzy logic reasoning following the error and error change, and the control mode parameters are adjusted in real time by particle swarm optimization following the error and error change. The step response simulation is used to simulate the control performance of the fault at the coal-rock interface. The simulation results show that the human-simulated intelligent control model proposed in this paper improves the stability time by 4.71 s, the rise time by 0.345 s, the peak time by 0.671 s, and the overshoot by 5.458 % compared with the original human-simulated intelligent control algorithm. The stability, rapidity, robustness and parameter optimization of the model proposed in this paper are better than those of other control models in system modal transformation, and have superior performance.