The rotational speed of the hydraulic turbine generator set will change with the load change of the power system, therefore, the speed control system of the unit needs to adjust its operating parameters in time according to the load change. The conventional PID control algorithm is widely used in the current hydraulic turbine speed control system, but it is unable to self-tune the parameters, which makes it difficult to achieve the desired control effect. In order to solve the above problems, this paper combines the neural network and fuzzy control to optimize the PID control parameters, and through the Matlab simulation experiments, it is verified that the control described in this paper can make the hydraulic turbine speed control system have satisfactory control effects in different operating conditions.