基于改进FNN-CCC的双伺服压力机同步控制策略研究

目的 改善双伺服压力机同步控制策略的动态响应性能和鲁棒性，提升双伺服压力机的单轴跟踪精度和双轴同步精度，实现成形过程的高精度位置控制。方法 建立双伺服压力机驱动系统数学模型，分析系统同步误差来源，结合模糊神经网络单轴控制算法，引入迭代学习律，设计一种改进模糊神经网络-交叉耦合(FNN-CCC)同步控制器。基于系统控制模型进行单轴阶跃响应特性与双轴正弦跟随特性仿真，搭建嵌入式双伺服压力机驱动系统试验平台，在偏载干扰条件下进行双轴同步控制试验，验证所提出理论的有效性。结果 仿真结果表明，与模糊控制算法和BP神经网络控制算法相比，该控制器单轴控制算法的超调量分别减少了11.5%和25.5%，调节时间分别减少了48.8%和34.4%，具有更好的动态响应性能。与原控制器相比，改进后的交叉耦合同步控制器最大双轴同步误差降低了65.7%，同步控制精度有所提高。试验结果表明，与传统PID-交叉耦合控制器相比，改进的FNN-CCC控制器有更好的控制性能，在热冲压合模成形阶段，单轴跟踪误差分别减小了81.8%和75.0%，双轴同步误差减小了69.2%。结论 所提出的同步控制策略在偏载干扰条件下具有较好的动态响应性能和鲁棒性，能够使同步误差快速收敛，提高了双伺服压力机驱动系统的单轴跟踪精度和双轴同步控制精度，实现了对双伺服压力机的高精度控制。

Synchronous Control Strategy of Dual Servo Press Based on Improved FNN-CCC

The work aims to improve the dynamic response performance and robustness of the synchronization control strategy of a dual servo press, enhance the single-axis tracking accuracy and dual-axis synchronization accuracy of the dual servo press, and achieve high-precision position control of the forming process. A mathematical model of the dual servo press drive system was established to analyze the sources of synchronization error in the system. Combining the fuzzy neural network single-axis control algorithm with iterative learning law, an improved fuzzy neural network-cross-coupling (FNN-CCC) synchronization controller was designed. Based on the system control model, single-axis step response characteristics and dual-axis sinusoidal tracking characteristics were simulated. An embedded dual servo press drive system test platform was built to conduct dual-axis synchronization control experiments under biased load interference to verify the effectiveness of the proposed theory. The simulation results showed that the single-axis control algorithm of the FNN-CCC controller had better dynamic response performance compared with fuzzy control and BP neural network control, with overshoots reduced by 11.5% and 25.5%, and adjustment times reduced by 48.8% and 34.4%, respectively. The maximum dual-axis synchronization error of the improved cross-coupling synchronization controller was reduced by 65.7% compared with the original controller, improving synchronization control accuracy. Experimental results showed that compared with the traditional PID-cross-coupling controller, the improved FNN-CCC controller had better control performance, reducing single-axis tracking errors by 81.8% and 75.0%, and dual-axis synchronization errors by 69.2% during the hot stamping forming stage. The proposed synchronization control strategy has good dynamic response performance and robustness under biased load interference, enabling rapid convergence of synchronization error and improving the single-axis tracking accuracy and dual-axis synchronization control accuracy of the dual servo press drive system, thereby achieving high-precision control of the dual servo press.