目的 为提升印后切纸机后挡规电液伺服系统在复杂工况下的动态响应速度、跟踪精度和抗干扰能力,提出一种基于改进粒子群优化（IPSO）的模糊PID控制策略。方法 在AMESim-Simulink多域联合仿真平台上,建立了阀控缸电液伺服数学模型,并设计双输入（误差及误差变化率）、三输出（ΔKp、ΔKi、ΔKd）的模糊PID控制器;采用IPSO对2个量化因子（Ke、Kec）和3个反量化因子（Kdp、Kdi、Kdd）进行全局寻优。结果 仿真结果表明,在阶跃响应测试中,将IFPID控制器的调节时间缩短至0.6 s,相较于传统PID,缩短了约67%;在正弦跟踪测试中,最大跟踪误差小于5 mm,降低了超过60%;在突变外力干扰下,可在0.9 s内恢复稳态,鲁棒性显著增强。结论 该控制策略具有良好的自适应和全局寻优能力,能够显著提升切纸机后挡规的控制精度和抗干扰能力,为切纸机的智能化控制提供了有效方法。
Abstract
The work aims to improve the dynamic response speed, tracking accuracy, and anti-interference capability of the electro-hydraulic servo system for the backgauge of post-press paper cutters by proposing a fuzzy PID control strategy based on Improved Particle Swarm Optimization (IPSO). On the AMESim-Simulink co-simulation platform, a mathematical model of the valve-controlled cylinder electro-hydraulic servo system was established. A fuzzy PID controller with two inputs (error and error rate) and three outputs (ΔKp, ΔKi, ΔKd) was designed, and IPSO was applied to globally optimize five parameters, including two scaling factors (Ke, Kec) and three de-scaling factors (Kdp, Kdi, Kdd). Simulation results showed that in step response tests, the IFPID controller reduced the settling time to 0.6 s, approximately 67% shorter than the conventional PID. In sinusoidal tracking tests, the maximum tracking error was less than 5 mm, reduced by more than 60%. Under sudden external disturbances, the system returned to steady state within 0.9 s, indicating significantly enhanced robustness. The proposed control strategy demonstrates strong self-adaptation and global optimization capabilities, significantly improving the control accuracy and robustness of the backgauge system, and providing an effective solution for the intelligent control of paper cutters.
关键词
切纸机 /
改进模糊PID /
改进粒子群算法 /
电液伺服系统 /
联合仿真
Key words
paper cutter /
improved fuzzy PID /
improved particle swarm optimization /
electro-hydraulic servo system /
co-simulation
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基金
北京印刷学院学院校级教学改革（创新重点）项目（20240027）; 北京印刷学院学科建设和研究生教育专项研究生课程项目（21090225001）
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