Aiming at the exoskeleton robot hydraulic joint drive system with nonlinear and uncertain parameters characteristics,which lead to modeling difficult and the uncertain impact disturbance problems with load,based on the characteristics of electro-hydraulic servo system,a mathematical model with elastic load as external load was established.In order to reduce the influence of impact disturbance term on force control,radial basis function (RBF) neural network was introduced to compensate the disturbance term,and a sliding mode force control strategy based on RBF neural network was designed.The feasibility of the model was further verified by the system characteristic,and the simulation test was compared.The results show that compared with PID control,the response time is shorter and the tracking error is reduced by 70.5%;under variable load conditions,the designed control strategy has better following ability and stronger robust performance,which can meet the force control requirements of the exoskeleton robot joint drive.The platform experiment further verifies the validity and correctness of the simulation results.