With the increasing requirements of industrial application on speed performance of servo system, the traditional PI controller could not meet the industrial demand for speed accuracy and robustness. Intelligent control algorithm can solve this problem. Based on the existing research and application, this paper applied the fuzzy control algorithm to the servo speed control system, which improved the accuracy and robustness of the system.In this thesis, DC motor was selected as the application object. The simulation platform of double closed loop speed control system was built on the basis of analyzing the mathematical model of the DC motor. Firstly, the PI controllers of the current loop and the speed loop were designed using engineering design method of the servo system. Through simulation experiments, the limitations of the traditional PI controller in regulating precision, response speed and anti-disturbance were verified. In order to further improve the performance of the servo system, a deep research was made on the control algorithm based on the fuzzy logic. This study focused on designing the Mamdani-type fuzzy controller and T-S type fuzzy controller, and discussed the impact of the input quantization factors and output scaling factors in Mamdani type fuzzy controller to system performance. Based on these, an adaptive fuzzy controller was designed. The speed performance of Mamdani-type fuzzy controller, T-S type fuzzy controller and adaptive fuzzy controller were compared to that of the traditional PI controller, which verified the advantages of fuzzy controller in improving the dynamic and static performance of the servo control system. Compared with the above mentioned three fuzzy controllers, the adaptive fuzzy controller could be used to adjust quantitative factors and scaling factors, which has better adaptability to the parameter changes of the control object.Finally, on the physical experiment platform of the DC speed control system, three fuzzy control algorithms were proposed and the related physical experiments were designed in this study. The experimental results are consistent with the simulation results, which verified the feasibility and effectiveness of fuzzy control algorithms. This indicated that the fuzzy control algorithms have high engineering practical significance. |