Research and Simulation Analysis of Fuzzy Intelligent Control System Algorithm for a Servo Precision Press

作     者：He, Yanzhong Luo, Xiang Wang, Xingsong 

作者机构：Southeast Univ Sch Mech Engn Nanjing 211102 Peoples R China 

出 版 物：《APPLIED SCIENCES-BASEL》 (Appl. Sci.)

年 卷 期：2024年第14卷第15期

页      面：6592页

核心收录：

基　　金：Key R&D Plan of Ningbo City, Zhejiang Province, China [2022Z035] Leading Army in Gusu, Suzhou City, Jiangsu Province, China [ZXL2023495] Leading park in Suzhou, Jiangsu Province, China [(2022)134] 

主　　题：press high-precision servo controller intelligent algorithm fuzzy control stability block diagram Simulink simulation 

摘      要：With the rapid development of the manufacturing industry toward intelligence and flexibility, traditional mechanical presses are unable to meet the increased stamping requirements due to the difficulties in achieving variable speed control and changing slide motion trajectories. Servo presses, driven directly by servo motors, can realize the flexible control of press movement and have become the trend in the industry for future development. The independent research and development of servo press control systems has become a popular topic and challenge in the domestic press industry. This paper proposes a new type of press transmission mechanism suitable for high-precision stamping, analyzes the working principle of its transmission mechanism, and provides a detailed analysis and discussion on the main research methods of fuzzy intelligent control for servo presses, including fuzzy model and basic control algorithms, fuzzy modeling and control of nonlinear systems, fuzzy predictive control, and stability analysis of fuzzy control systems. Based on the principle of the control scheme, a closed-loop control system block diagram and mathematical model for servo high-precision presses are established. Taking the physical prototype parameters of the STSZG1-250 as an example, the control system is dynamically simulated and verified using Simulink modules. Finally, their role and effects in intelligent control, and prospects for the development of fuzzy intelligent control, are discussed.