Affiliations: [a] Schools of Mechanical Engineering, Shenyang Jianzhu University, Shenyang, China
| [b] Institute of Science and Technology, Shenyang Jianzhu University, Shenyang, China
| [c] Graduate School, Shenyang Jianzhu University, Shenyang, China
Abstract: According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. The fuzzy neural network predictive control technology can be used to control the tool hydraulic system of Tunnel Boring Machine.
Keywords: Neural network, fuzzy neural network, predictive control, fuzzy control, tool hydraulic control system
