In order to improve the actuator precision,a method for eliminating nonlinear and no-smooth hysteresis characteristic of piezoceramic actuator was proposed.An inner product-based dynamic neural network nonlinear and no-smooth hysteresis inverse model for piezoceramic was established,in which the feedback error learning method was used to avoid obtaining Jacobian information of piezoceramic by positive model.On dSPACE system platform,a neural networks adaptive inverse control was realized combined with a PID control.In order to satisfy the requirement of real time control,the program was designed by a high efficiency and fast C-MEX S function.The experimental results indicate that the precision of the proposed adaptive inverse control based on neural networks is 0.13 μm and PID control precision is 0.32 μm.It is shown that the proposed control method can remove effectively the hysteresis characteristic of piezoceramic and has higher control precision.