Aiming at the problem of force control when industrial robots clamped workpiece for grinding, a robot force control method based on neural network algorithm was proposed, a set of industrial robot grinding system was built, and the corresponding upper computer software was developed under the environment of Visual Studio. By analyzing the principle of neural network algorithm, the structure of neural network was designed, and the training data obtained from actual grinding process was used for neural network training.The force signal collected in real time by the force sensor was output to the trained neural network model, the trajectory correction value of the robot grinding machining was predicted and passed to the robot,to real-time correct grinding trajectory, so as to realize the indirect force control of the industrial robot. Finally, the force tracking experiment and titanium alloy grinding experiment were carried out on the industrial robot grinding system, which verified the validity and practicability of the proposed force control method and the robot grinding system.