期刊文献+

铣削过程在线辨识与极点配置自适应控制 被引量:3

ON LINE IDENTIFICATION AND POLE ASSIGNMENT ADAPTIVE CONTROL FOR MILLING PROCESS
下载PDF
导出
摘要 研究了铣削加工过程的建模、参数在线辨识及自适应控制问题,为铣削过程建立了二阶离散传递函数模型,提出了一种修正的带遗忘因子递推最小二乘参数辨识算法,从而解决了普通递推最小二乘辨识算法中由于递推计算协方差矩阵衰退或膨胀引起辨识结果失真的问题,采用极点配置设计原理,为铣削过程推导了自适应控制的控制律。仿真和实验表明,修正的最小二乘辨识算法和极点配置自适应控制律是正确和可靠的,自适应控制器可获得所需的响应性能。 This paper investigates modeling, on line parameter identification and adaptive control for the milling process. A second order discrete time transfer function is derived for the milling process. Based on the ordinary recursive least squares, a modified identification algorithm is suggested so as to eliminate the parameter distortion caused by the degeneration or expansion of the covariance matrix. The adaptive control law for the milling process is developed using pole assignment principle according to the desired objective transfer function of the closed loop system including the adaptive controller and the process. A PC/DSP based adaptive control system is built up to verify the algorithms of the adaptive controller. The modified recursive least squares and the pole assignment adaptive control law are plugged into a real time software platform, Intelligent Machining Modules(IMM), as plug in modules(PIMs) written in ANSI C codes. The simulation and experiment have demonstrated that the algorithms for identification and adaptive control are stable, reliable and robust. The milling process controlled by the adaptive controller behaves with the desired performance.
出处 《航空学报》 EI CAS CSCD 北大核心 1999年第5期435-439,共5页 Acta Aeronautica et Astronautica Sinica
基金 国家自然科学基金
关键词 铣削加工 自适应控制 在线辨识 极点配置 milling process CNC adaptive control on line identification modified RLS pole assignment
  • 相关文献

参考文献3

  • 1孙增圻.计算机控制理论与应用[M].北京:清华大学出版社,1989.115-116.
  • 2孙增圻,计算机控制理论与应用,1989年,115页
  • 3史维祥,系统辨识,1989年,34页

共引文献3

同被引文献13

  • 1鲁宏伟,吴雅,杨叔子.快速采样数据建模的最小二乘算法[J].华中理工大学学报,1994,22(7):44-48. 被引量:1
  • 2张立民.人工神经网络的模型及应用[M].上海:复旦大学出版社,1993.
  • 3Chen Yung-yaw, Huang Pai-yi, Yen Jia-yush. Frequency-domain identification algorithms for servo systems with friction[J]. IEEE Transactions on Control Systems Technology, 2002, 10(5): 654-665.
  • 4Kueiming Lo, Kimura H. Recursive estimation methods for discrete systems[J]. IEEE Transactions on Automatic Control, 2003, 48(11): 2019-2023.
  • 5Ulsoy A G,Koren K.Control of machining process [J].Journal of Dynamic Systems Measurement and Control,1993,115(6):301-308.
  • 6Tomizuka M,Oh J H,Dornfeld D A.Model reference adaptive control of the milling process[A].Hardt D E,Book W J.Control of Manufacturing Process and Robotic Systems [C].New York:ASME,1983.37-44.
  • 7Dameshmend L K,Pak H A.Model reference adaptive control of cutting force in milling [A].Dynamic Systems:Modeling and Control [C].New York:ASME,1985.43-50.
  • 8Altintas Y.Direct adaptive control of end milling process [J].Int J Mach Tools Manufact,1994,34(4):461-474.
  • 9任琪.基于神经网络PID控制的交流伺服系统[J].微计算机信息,2008,24(13):117-118. 被引量:4
  • 10陈虎,韩至骏.铣削自适应控制系统中的工况识别技术[J].清华大学学报(自然科学版),1999,39(2):39-42. 被引量:1

引证文献3

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部