Study On The Synchronous Method Of Double-cylinder Forging Hydraulic Press Based On Immune Neural Networks PID Algorithm

Hydraulic technology is widely used in the engineering, Synchronization control has been an important issue in hydraulic industry, With the development of the aerospace and modern machinery and processing industries, Metal processing equipment, metallurgical machinery, construction machinery and other drive device is very urgent requirement of high-precision double-cylinder hydraulic synchronization technology。 But there are many factors that affect the synchronization of double-cylinder servo system, such as uneven loads, leakage, friction, resistance, different structural elastic deformation, hydraulic oil, etc。 So it is very important to research with Hydraulic synchronization control technology。This paper design a double-cylinder forging hydraulic system based on Synchronous control system synchronization works and work process requirements. The system transfer function is deduced through the establishment of key hydraulic components of the system mathematical model, Then the dynamic performance of the system to be analyzed. The simulation model of the system is established in MATLAB/Simulink by system model. Since the double-cylinder electro-hydraulic servo synchronization control system is a complex nonlinear time-varying systems, the prevalence of parameter changes, and the requirements of the synchronous control of high precision, response quickly, small overshoot. Traditional PID controller which has the defects of can’t change parameter variations and difficult to select, not that effective when apply on this kind of servo object, new servo strategy must be found to adjust the requirement above.The immune algorithm combined with traditional PID algorithm, based on double-cylinder forging hydraulic press control requirements. The author also introduces the BP neural network with any approximation of the nonlinear function to build antibodies inhibit adjustment function in immune PID algorithm. Immune neural network PID controller designed for double-cylinder forging hydraulic synchronization control system. Simulations results show that immune neural network PID controller have more accurate, smaller error, more robustness than the PID controller. Meet the double-cylinder forging hydraulic synchronization control system control requirements, and can be applied to double-cylinder forging hydraulic synchronization control system.