Because of the nonlinear of electrohydraulic servo system, PID control is difficult to control the system model. An electrohydraulic servo system model composed of hydraulic servo valve and hydraulic cylinder was constructed, and cuckoo search algorithm (CSA) and genetic algorithm (GA) were used to realize the model predictive control (MPC) of the electrohydraulic servo system.According to the continuous state space model, the force identification model was established, and the hydraulic cylinder and black box were modeled mathematically.CSA and GA algorithms were used to optimize MPC control and adjust parameters to improve the stability and control performance of the system model.Simulation experiments were carried out on the external force, voltage and amplitude signals of the system model, and comparison was made with PID control.The results show that, compared with PID control, the overshot of the external force under MPC control of CSA and GA is reduced by 20%, the fluctuation error of voltage is reduced by 1.5 V, and the tracking steadystate error of the amplitude is reduced by 50%.It is shown that the MPC control method of CSA and GA is adopted to improve the robustness and stability of the electrohydraulic servo system, with high tracking accuracy and dynamic performance of the system.