磁悬浮无尘传送系统辨识与优化控制研究

发布时间：2018-04-28 00:30

本文选题：永磁悬浮 + 无尘传送　；参考：《沈阳工业大学》2017年硕士论文

【摘要】：随着科学技术的不断发展,在现代信息产业和高精密加工等领域,如集成电路制造,半导体系统及医疗器械加工等场合对超洁净生产环境等提出了越来越苛刻的要求。在物品的搬运上,传统的机械手受距离的限制,气垫搬运设备也很难做到绝对的无尘传送,并且在节能方面也有欠缺。磁浮技术自本世纪六十年代发展至今,以其节能、高效、无环境污染等独特优点在工业、军事和民用等各个领域获得了长足的进展。因此,磁悬浮技术无接触,无需润滑的特点是可以达到生产环境无污染,超洁净的目的的。但是,高能耗、高建设成本的电磁悬浮技术一直是制约其稳固发展的重要因素。为了达到节约能源、降低成本的目的,一种新型的永磁悬浮无尘传送系统被提出。该系统具有磁悬浮系统普遍存在的非线性及高耦合的特点,应用传统的数学建模方式对其建立的动力学方程并不能很好的反映实际永磁悬浮系统的各项特性,不能准确的描述系统各项性能指标与动态特性,而系统辨识的方法可以直接根据实验采集的输入输出数据得到与系统特性等价的数学模型,这就很好的解决了此问题。因此,本文针对单自由度磁悬浮支撑机构与永磁悬浮无尘传送系统的结构特点,应用最小二乘辨识方法对其进行系统辨识,得出最接近真实系统的传递函数模型与状态空间方程。由于该模型与真实系统最为接近,故不稳定性较强,为了解决系统无法实现悬浮物在悬浮气隙变化较大时的稳定控制问题,根据自适应控制方法与变结构控制的原理和思想,提出了一种滑模变结构自适应控制方法,并设计相应的自适应控制器。仿真分析结果表明,该自适应控制器可以很好的控制由系统辨识得出的传递函数模型,并且由系统辨识得出的该模型在响应速度方面、准确性方面、稳定性方面均有良好的响应,该滑模变结构自适应控制器可以很好的解决悬浮物在悬浮气隙变化较大时的稳定控制问题。为了验证上述滑模变结构自适应控制器的控制性能,针对单自由度磁悬浮控制系统实验平台,对上述控制器进行了与仿真分析相同的实验验证。实验结果与仿真分析结果基本一致,证实了通过系统辨识得出的传递函数模型,与真实系统最为接近并且可以通过自适应控制器很好的控制系统的各项性能指标。
[Abstract]:With the development of science and technology, more and more stringent requirements have been put forward in the field of modern information industry and high-precision machining, such as integrated circuit manufacturing, semiconductor system and medical device processing, etc. In the handling of goods, the traditional manipulator is limited by the distance, the air cushion handling equipment is also difficult to achieve absolute dust-free transport, and there is also a lack of energy saving. Maglev technology has been developed since 1960s, and has made great progress in industrial, military and civil fields with its unique advantages of energy saving, high efficiency and no environmental pollution. Therefore, the magnetic levitation technology has no contact and no lubrication. It can achieve the goal of no pollution and super-cleanliness. However, high energy consumption and high construction cost are the important factors restricting its steady development. In order to save energy and reduce cost, a new permanent magnetic levitation dustless transmission system is proposed. The system has the characteristics of nonlinearity and high coupling of magnetic levitation system. The dynamic equations established by the traditional mathematical modeling method can not well reflect the characteristics of the real permanent magnetic levitation system. The system can not accurately describe the performance indicators and dynamic characteristics, and the system identification method can be directly based on the input and output data collected from the experiment to get the mathematical model equivalent to the system characteristics, which solves this problem very well. Therefore, according to the structure characteristics of single degree of freedom magnetic levitation support mechanism and permanent magnetic levitation dust-free transmission system, the least square identification method is used to identify the system. The transfer function model and state space equation which are closest to the real system are obtained. Because the model is most close to the real system, it is unstable. In order to solve the problem of the stability control of the suspended matter when the air gap changes greatly, the adaptive control method and the principle and idea of variable structure control are used to solve the problem. A sliding mode variable structure adaptive control method is proposed and the corresponding adaptive controller is designed. The simulation results show that the adaptive controller can well control the transfer function model identified by the system, and the response speed and accuracy of the model can be obtained by the system identification. The sliding-mode variable structure adaptive controller can solve the stability control problem of suspensions when the air gap changes greatly. In order to verify the control performance of the sliding mode variable structure adaptive controller, the experimental platform of the single-degree-of-freedom maglev control system is used to verify the performance of the controller in the same way as the simulation analysis. The experimental results are in good agreement with the simulation results. It is proved that the transfer function model identified by the system is the closest to the real system and can be used to control the performance of the system through the adaptive controller.
【学位授予单位】：沈阳工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH22

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