## 1 Introduction
According to the control requirements of synchronization error and tracking error, a simultaneous control scheme for the forging hydraulic press is established, and a novel fuzzy compensation forging hydraulic press synchronization controller design algorithm is further provided to realize forging hydraulic press notification. However, the timeliness of this algorithm control is poor [PERSON] proposed a synchronous control method for a two-cylinder forging hydraulic press based on new fuzzy reasoning [PERSON] (2015). This method can design the internal circuit of the two-cylinder forging hydraulic press, reduce the delay of hydraulic machine control, and realize the synchronous control of the two-cylinder forging hydraulic press. However, this method controls the accuracy in general. In order to solve the problems of the above algorithm, a synchronous control algorithm of double cylinder forging hydraulic press based on a fuzzy neural network is proposed. The transfer function of the valve-controlled cylinder of the double-cylinder forging hydraulic press is deduced by using the flow equation of the valve, the flow balance equation of the cylinder and the force balance equation. According to the function, the mathematical model of the synchronous control of the double-cylinder forging hydraulic press is constructed. The conventional fuzzy neural network is optimized by introducing the compensation operation, and the improved neural network is used to synchronize the control of the double-cylinder forging hydraulic press. The realization of this algorithm makes the double steel forging hydraulic press more efficient and intelligent, can greatly improve production efficiency, reduce production costs, and increases the ability to deal with faults intelligently. The overall structure of the algorithm is as follows:  
(1) Through the mathematical modeling of the various components of the double cylinder forging hydraulic press, a complete mathematical modeling of the entire double cylinder forging hydraulic press was carried out. (2) According to the implementation process of the fuzzy neural network algorithm, the fuzzy neural network algorithm is used to realize the synchronous control of the double cylinder forging hydraulic press. (3) Experimental results and analysis. Through experimental data, the feasibility and effectiveness of the fuzzy neural network algorithm for synchronous control of a double-cylinder forging hydraulic press are demonstrated. (4) Based on the existing research of the paper, the prospects are put forward. Synchronization Control Algorithm of Double-Cylinder Forging Hydraulic Press Based on Fuzzy Neural Network  
Due to the time-varying and non-linear influence of the position servo system of the two-cylinder forging hydraulic press, the synchronization accuracy of the two-cylinder forging hydraulic press is affected by many factors, such as the manufacturing accuracy of the hydraulic cylinder [10; 11; 12], the uneven load of the system, the influence of external conditions such as temperature, etc. [13]. The synchronization accuracy of the two-cylinder forging hydraulic press has many influential and complex factors, which makes the control of the two-cylinder forging hydraulic press more difficult. Based on a fuzzy neural network, the synchronous control algorithm of two-cylinder forging hydraulic press is developed based on the mathematical model construction [14]. Based on the fuzzy neural network-based two-cylinder forging hydraulic machine synchronous control algorithm, the two-cylinder forging hydraulic machine synchronous control is realized. The overall control flow of the algorithm is shown in Figure 1.