Oiling quantity control of the traditional sintering machine table wheels oiling system has problems such as low control accuracy and poor robustness,which can no longer meet the demand for accurate oiling. In order to improve the oiling performance,an intelligent control method of sintering machine table wheels oiling quantity based on the improved grey wolf algorithm (IGWO) was proposed. MATLAB software was used to identify the mathematical model of the oiling quantity control system;then,a BP neural network PID oiling quantity control system was built.In order to improve the convergence speed of the grey wolf algorithm,a non-linear convergence factor and dynamic weights were introduced,and the IGWO algorithm was designed to realize the optimal initial values and thresholds of the BP neural network,and the optimal PID control parameters were output. Finally,the control effects before and after optimization with the IGWO algorithm were compared in simulation environment. The research results show that the designed PID controller has low overshoot and high control accuracy,which can realize the intelligent control of oiling quantity and meet the demand of precise oiling.