| 李学军,黎耀强,蒋玲莉,李家皇,张茜.基于NRBO算法优化的模糊PID轴承预紧力控制[J].电子测量与仪器学报,2025,39(7):227-235 |
| 基于NRBO算法优化的模糊PID轴承预紧力控制 |
| Bearing preload control based on fuzzy PID controlleroptimized by NRBO algorithm |
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| DOI： |
| 中文关键词: 轴承预紧力 NRBO算法 模糊PID 预紧力控制 |
| 英文关键词:bearing preload NRBO algorithm fuzzy PID pre-tightening force control |
| 基金项目:国家自然科学基金项目(52275094)、广东省基础与应用基础研究基金区域联合基金重点项目(2024B1515120033)、广东省普通高校创新团队项目(2023KCXTD031)资助 |
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| Author | Institution |
| Li Xunjun | School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan 528000,China |
| Li Yaoqiang | School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan 528000,China |
| Jiang Linli | School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan 528000,China |
| Li Jiahuang | School of Mechanical and Electrical Engineering and Automation, Foshan University, Foshan 528000,China |
| Zhang Xi | Wafangdian Bearing Group Corp., Ltd., Dalian 116399,China |
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| 中文摘要: |
| 合适的预紧力可以使轴承系统达到减少系统振动和噪音、提高轴承刚度的目的,为满足轴承预紧力控制的需要,提出了基于牛顿-拉夫森优化算法（NRBO）优化模糊PID的预紧力控制策略。首先,确定轴承预紧力液压加载的方式以及建立传递函数;其次,结合AMESim/Smilink的联合仿真模型,并与常规PID,模糊PID、粒子群算法（PSO）优化模糊PID进行了仿真对比;最后,开展了试验验证。仿真结果表明，NRBO算法优化模糊PID对比常规PID、模糊PID和PSO算法优化模糊PID超调量分别减少42.93%、27.78%、13.91%,调节时间分别减少了3、2.3、1.6 s。试验结果表明，轻载、中载、重载的径向力作用下,NRBO优化模糊PID控制器相比于常规PID控制器，调节时间分别减少5.3、10.4、4.5 s,超调量分别减少43.78%、52.52%、72.36%;相比于模糊PID控制器调节时间分别减少2.7、5.2、2.6 s,超调量分别减少29.62%、46.24%、59.52%;相比PSO算法优化模糊PID控制器调节时间分别减少1.7、3.2、2.3 s,超调量分别减少17.38%、30.02%、55.42%。表明了NRBO优化模糊PID控制器拥有更快、更精确的控制效果,能够很好的实现预紧力的精确施加。 |
| 英文摘要: |
| Appropriate preload can make the bearing system achieve the purpose of reducing system vibration and noise and improving bearing stiffness. In order to meet the needs of bearing preload control, a preload control strategy based on NRBO algorithm to optimize fuzzy PID is proposed. Firstly, the hydraulic loading method of bearing preload is determined and the transfer function is established. Secondly, combined with the co-simulation model of AMESim/Smilink, and compared with conventional PID, fuzzy PID, PSO optimized fuzzy PID. Finally, the experimental verification is carried out. The simulation results show that the overshoot of fuzzy PID optimized by NRBO algorithm is reduced by 42.93%, 27.78% and 13.91% respectively compared with conventional PID, fuzzy PID and PSO algorithm, and the adjustment time is reduced by 3, 2.3 and 1.6 s respectively. The test results show that under the radial force of light load, medium load and heavy load, compared with the conventional PID controller, the NRBO optimized fuzzy PID controller reduces the adjustment time by 5.3, 10.4 and 4.5 s respectively, and the overshoot is reduced by 43.78%, 52.52% and 72.36% respectively. Compared with the fuzzy PID controller, the adjustment time is reduced by 2.7, 5.2 and 2.6 s respectively, and the overshoot is reduced by 29.62%, 46.24% and 59.52% respectively. Compared with the PSO algorithm to optimize the fuzzy PID controller, the adjustment time is reduced by 1.7, 3.2, 2.3 s, and the overshoot is reduced by 17.38%, 30.02%, and 55.42%, respectively. It shows that the NRBO optimized fuzzy PID controller has faster and more accurate control effect, and can achieve accurate application of preload. |
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