大型复合板材恒压砂带磨削模糊自适应控制技术研究及应用
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摘要
随着工业过程日益走向大型化、连续化、复杂化,很多系统使用常规控制无法得到满意的控制效果。同样,作为工件的大型复合板材通过爆炸接合后一般表面平面度很差,校正后仍然存在不同程度的翘曲变形,使表面呈波浪状。采用传统控制的平面磨削,磨头不能较好跟随工件型面变化,磨削时易出现在工件突起处过量磨削和在工件凹谷处磨削不到的磨削不均匀现象,这样磨削出来的工件表面质量差,其性能也满足不了实际的使用要求。另外,传统的控制方式往往需要建立被控对象的精确数学模型,而这在实际生产过程中也是很难做到的。
为了更好的使得磨削加工过程中磨头磨具快速有效地跟随板材型面起伏变化,控制其恒压力接触被磨工件,防止出现工件部分位置磨削加工不到位或过磨的现象,以保证其磨削深度尺寸和磨削加工表面质量,因此结合砂带磨削和模糊自适应控制的诸多优点,本论文在阅读和研究大量国内外相关领域文献和平面砂带磨削工业控制加工的背景下,开展了针对大型复合板材恒压砂带磨削模糊自适应控制技术研究及应用。
主要内容及研究成果如下:
①分析大型复合板材在磨削加工中存在的问题,将自适应模糊控制技术引入平面砂带磨床的控制系统中,对平面恒压砂带磨床控制系统算法策略进行研究,研究了控制系统采用模糊自适应控制算法的必要性和可行性。
②结合平面砂带磨床磨头磨削机构和控制系统,研究并建立系统控制对象数学模型,并进行简化和工程化处理。
③根据平面砂带磨床磨削控制特点,提出了模糊控制规则和控制算法。详细分析了模糊化和解模糊方法,并对模糊控制规则进行了优化,保证控制系统具有良好的实时性。
④设计了大型平面砂带磨床的自适应模糊控制器,确立了模糊化和解模糊的方法,并建立了模糊控制规则表,根据误差E和误差变化EC直接查找查询表,最终采用单片机来保证控制系统的恒压磨削。并运用MATLAB进行仿真,观察分析平面磨床模糊自适应控制系统的快速跟随性、稳定性和鲁棒性等。
⑤分析并设计试验装置,搭建大型平面砂带磨床恒压模糊自适应控制的试验平台。
With the rapid growth of industrial processes toward large size, continuous and complex, the control effect of many systems can’t be satisfied when using the conventional control. Similarly, parallelism of the surface of large composite plates are very poor after connecting by explosion, even it’s have different degrees of warpage after correction, so that the surface of the composite plates are like the wavy. Using the traditional control of surface grinding, the grinding head can not be better to follow the changes of the workpiece’s surface, the phenomenon of uneven grinding is appeared very easy. so the quality of the surface of workpiece is poor, which has failed to meet the actual requirements. In addition, the traditional control methods often need to establish accurate mathematical model of controlled object, which in the actual production process is very difficult to do.
In order to effectively solve the problems of abrasive tools change with plate surface, constant pressure contact with workpiece to control grinding depth and grinding not enough or grinding too depth in some position, raising the surface grinding quality. In the paper, many advantages are incorporated of abrasive belt grinding and fuzzy adaptive control, the research and application of fuzzy adaptive constant pressure abrasive belt grinding technologies for large-scale complex plates were studied on the basis of referencing a lot of related literatures home and abroad .
Main research contents and conclusions are as follows:
①Problems of the large-scale composite plants by the grinding have been analyzed. Algorithm strategy of flat belt grinding machine control system has been studied in accordance with abrasive belt grinding machine control characteristics and the present treatment methods commonly used. The necessity and feasibility of fuzzy adaptive control algorithm system was given.
②According to the requirements of flat grinding machine and control system, the controlled object is researched, and at the same time, the mathematical model of the system is treated, and then it’s processed simplify and engineering.
③According to the control characteristics of flat grinding machine, the fuzzy control rules and control algorithms are proposed. The method of fuzzy is analysized, and the fuzzy control rules are optimized, in order to ensure the control system has a good real time.
④Fuzzy adaptive controller of large-scaled flat belt grinding is designed, the method of fuzzy and fuzzy control rule table are established. The control rule table is looked up directly based on the error E and error change EC, and then the single chip is used to ensure the control system to grind with constant pressure. And the MATLAB simulation is used to observe and analyze the following, stability and robustness of fuzzy adaptive control system of flat belt grinding machine.
⑤Test equipment is analyzed and designed, and the test platform of fuzzy adaptive control with constant pressure of large flat belt grinding machine was set up.
为了更好的使得磨削加工过程中磨头磨具快速有效地跟随板材型面起伏变化,控制其恒压力接触被磨工件,防止出现工件部分位置磨削加工不到位或过磨的现象,以保证其磨削深度尺寸和磨削加工表面质量,因此结合砂带磨削和模糊自适应控制的诸多优点,本论文在阅读和研究大量国内外相关领域文献和平面砂带磨削工业控制加工的背景下,开展了针对大型复合板材恒压砂带磨削模糊自适应控制技术研究及应用。
主要内容及研究成果如下:
①分析大型复合板材在磨削加工中存在的问题,将自适应模糊控制技术引入平面砂带磨床的控制系统中,对平面恒压砂带磨床控制系统算法策略进行研究,研究了控制系统采用模糊自适应控制算法的必要性和可行性。
②结合平面砂带磨床磨头磨削机构和控制系统,研究并建立系统控制对象数学模型,并进行简化和工程化处理。
③根据平面砂带磨床磨削控制特点,提出了模糊控制规则和控制算法。详细分析了模糊化和解模糊方法,并对模糊控制规则进行了优化,保证控制系统具有良好的实时性。
④设计了大型平面砂带磨床的自适应模糊控制器,确立了模糊化和解模糊的方法,并建立了模糊控制规则表,根据误差E和误差变化EC直接查找查询表,最终采用单片机来保证控制系统的恒压磨削。并运用MATLAB进行仿真,观察分析平面磨床模糊自适应控制系统的快速跟随性、稳定性和鲁棒性等。
⑤分析并设计试验装置,搭建大型平面砂带磨床恒压模糊自适应控制的试验平台。
With the rapid growth of industrial processes toward large size, continuous and complex, the control effect of many systems can’t be satisfied when using the conventional control. Similarly, parallelism of the surface of large composite plates are very poor after connecting by explosion, even it’s have different degrees of warpage after correction, so that the surface of the composite plates are like the wavy. Using the traditional control of surface grinding, the grinding head can not be better to follow the changes of the workpiece’s surface, the phenomenon of uneven grinding is appeared very easy. so the quality of the surface of workpiece is poor, which has failed to meet the actual requirements. In addition, the traditional control methods often need to establish accurate mathematical model of controlled object, which in the actual production process is very difficult to do.
In order to effectively solve the problems of abrasive tools change with plate surface, constant pressure contact with workpiece to control grinding depth and grinding not enough or grinding too depth in some position, raising the surface grinding quality. In the paper, many advantages are incorporated of abrasive belt grinding and fuzzy adaptive control, the research and application of fuzzy adaptive constant pressure abrasive belt grinding technologies for large-scale complex plates were studied on the basis of referencing a lot of related literatures home and abroad .
Main research contents and conclusions are as follows:
①Problems of the large-scale composite plants by the grinding have been analyzed. Algorithm strategy of flat belt grinding machine control system has been studied in accordance with abrasive belt grinding machine control characteristics and the present treatment methods commonly used. The necessity and feasibility of fuzzy adaptive control algorithm system was given.
②According to the requirements of flat grinding machine and control system, the controlled object is researched, and at the same time, the mathematical model of the system is treated, and then it’s processed simplify and engineering.
③According to the control characteristics of flat grinding machine, the fuzzy control rules and control algorithms are proposed. The method of fuzzy is analysized, and the fuzzy control rules are optimized, in order to ensure the control system has a good real time.
④Fuzzy adaptive controller of large-scaled flat belt grinding is designed, the method of fuzzy and fuzzy control rule table are established. The control rule table is looked up directly based on the error E and error change EC, and then the single chip is used to ensure the control system to grind with constant pressure. And the MATLAB simulation is used to observe and analyze the following, stability and robustness of fuzzy adaptive control system of flat belt grinding machine.
⑤Test equipment is analyzed and designed, and the test platform of fuzzy adaptive control with constant pressure of large flat belt grinding machine was set up.
引文
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[2]赵树萍,吕双坤.钛合金在航空航天领域中的应用[J].钛工业进展,2002,(6):18-21.
[3]高英杰.钛及钛合金平面磨削加工工艺研究[J].稀有金属快报. 2006, 25(10):33-35.
[4]石磊.钛合金切削加工中刀具与工件性能匹配的研究[D].济南:山东大学硕士学位论文,2007.
[5]雷宇晓,陈宗帖,陈家权等.平面磨床试验研究[J].制造技术与机床. 2007,(2):25-28.
[6]杨辉.超精密平面磨床关键技术的发展[J].机械工艺师. 2001,(1):17-19.
[7]许庆顺.钛合金板材砂带恒压抛磨过程型面自适应控制技术研究[D].重庆:重庆大学硕士学位论文. 2008.
[8]闾志明.大型复合板材自适应恒压砂带磨削关键技术研究[D].重庆:重庆大学硕士学位论文. 2010.
[9] Zadeh L A. Fuzzy Sets[J]. Information and Control, 1965, 8(3):338-353.
[10]黄云黄智著.现代砂带磨削技术及工程应用[M].重庆:重庆大学出版社,2009.
[11] HUANG ZHI, HUANG YUN, et al. Finishing advanced surface of Magnesium alloy tube based on abrasive belt grinding Technology [J]. Materials science Forum. 2009, 610(1):975-978.
[12] HUANG YUN, HUANG ZHI. Research on the Heavy Abrasive Belt Grinding Machine to reduce Thickness of Engine Connecting Rod Head[J]. Key Engineering Materials. 2006, 4(2):436-440.
[13]王维朗,潘复生.砂带磨削技术及材料的研究现状和发展前景[J].材料导报, 2002, 20(2):106-108.
[14]倪德荣.谈谈大平面磨床磨削时所遇到的问题[J].机床与工具. 1995,12.
[15]张培根,陈国宏,郑三中等.变力随形修磨原理[J].兰州铁道学院学报.1999,(6):59～64.
[16] Y.M.Ali and L.C.Zhang. A fuzzy model for predicting burns in surface grinding of steel [J]. International Journal of Machine Tools and Manufacture. 2004, 44(5):563-571.
[17] W.Konigt, Y.Altintast and F.Memist. Direct adaptive control of plunge grinding process using acoustic emission (AE) sensor [J]. International Journal of Machine Tools and Manufacture. 1995, 35(10):1445-1457.
[18] L.Guo,A.Schone, X.Ding. Grinding force control using nonlinear adaptive strategy[J].Control Engineering Practice. 1995, 3(1):459-462.
[19] Sungchul Jee,Yoram Koren. Adaptive fuzzy logic controller for feed drives of a CNC machine tool [J]. Mechatronics. 2004, 14 (2): 299–326.
[20] Markus Hirvonen, Olli Pyrhonen, Heikki Handroos. Adaptive nonlinear velocity controller for a ?exible mechanism of a linear motor[J]. Mechatronics. 2006, 16 (1): 279–290.
[21] Romain Postoyan, Tarek Ahmed-Ali, Laurent Burlion,et al. On the Lyapunov-based adaptive control redesign for a class of nonlinear sampled-data systems[J]. Automatica. 2008, 44 (18): 2099–2107.
[22] M. Mahfouf, D. A. Linkens and M. F. Abbod. Adaptive fuzzy TSK model-based predictive control using a carima model structure[J]. Institution of Chemical Engineers Trans IChemE. 2000, 78(1):590-596.
[23] Ulsoy, A. Galip. App lications of adaptive control to machine tool process control [J]. IEEE Control Systems Magazine, 1989, 9(4):33-37.
[24] Shyu KK, Lai CK, Tsai YW, Yang DI. A newly robust controller design for the position control of permanent—magent synchronous motor[J]. IEEE TRANSYCTIONS ON INDUSTRIAL EL ECTRONICS. 2002, 49(3):558～565.
[25] S.P. Moustakidis, G.A.Rovithakis, J.B.Theocharis. An adaptive neuro-fuzzy tracking control for multi-input nonlinear dynamic systems[J]. Automatica. 2008, 44 (2):1418–1425.
[26] Xin Wang, Shaoyuan Li, Wenjian Cai, et al. Multi-model direct adaptive decoupling control with application to the wind tunnel system[J]. ISA Transactions . 2005, 44(1):131–143.
[27]刘贵杰,巩亚东,王宛山.基于交流异步电机驱动磨床进给位移的自学习控制[J].东北大学学报. 2001,22(3):268-270.
[28]郑国强.无心通磨加工的自适应控制[J].洛阳工学院学报. 2001,(9):19-21.
[29]黄民双,曾励等.用IBM-PC机实现切入式磨床的自适应预报控制系统[J].现代机械. 1999,(1):22-24.
[30]王家忠,周桂红,王龙山等.外圆纵向磨削自适应控制器[J].机床与液压. 2008, 36(4):244-246.
[31]王家忠.外圆纵向智能磨削关键技术研究[D].长春:吉林大学博士学位论文, 2006.
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