In view of the large tracking error of hydraulic driving piston motion and pressure accuracy, a neural network fuzzy sliding mode control is designed and the control accuracy is verified by simulation.The driving plane diagram of the hydraulic cylinder was created, and the internal parametric variation equation of the hydraulic cylinder chamber was deduced. The change of driving pressure and position of hydraulic cylinder was analyzed, and the transformation equations of input and output were established by using linear model. Using the sliding mode control method, the neural network algorithm was used to approach the sliding mode control, and the fuzzy switching rule was used to adjust the sliding mode control adaptively. MATLAB was used to simulate and verify the hydraulic cylinder piston track and chamber pressure tracking, and the output effect was compared and analyzed with the sliding mode control. The results show that the tracking error of piston motion track and chamber pressure is larger by using sliding mode control method, while the tracking error of piston motion track and chamber pressure is smaller by using neural network fuzzy sliding mode control method. By using the neural network fuzzy sliding mode control method, the hydraulic cylinder control system has a strong adaptive regulation ability, thus improving the piston motion track and chamber pressure tracking accuracy.