Taking surgical robot slavehand as research object, adaptive control based on block approximation was completed to the surgical robot slavehand based on radial basis function (RBF) neural network. Aiming at the inaccurate modeling for the surgical robot slavehand, RBF neural network was used to segment the three coefficients matrixes from the slavehand mechanics model respectively, and the actual dynamics model of the slavehand was obtained. At the same time,control law was adjusted dynamically to achieve stable and adaptive control of the system. Based on the stability analysis of the algorithm, the simulation experiment was completed. Experimental results show that the proposed control algorithm improves the system control performance and has the characteristics of high precision, good stability and strong robustness.