The uncertainties existing in robot models present difficulties to controlling robots precisely. This is especially obvious in robot force control, and limits the usage of robot force control in industry field. Intelligent control, such as fuzzy control and neural network, is an effective method to solve this problem faced by classical control methods. Unsupervised learning network was adopted to compensate the uncertainties existing in robot impedance control online and to improve the performance of force tracking. The effectiveness of the proposed neural algorithm is verified by a simulation.