Active disturbance rejection control for PMLM servo system in CNC machining

详细信息    查看全文

• 作者：Jianxin Guo ; Wenchao Xue ; Tao Hu
• 关键词：Active disturbance rejection control ; CNC machine ; nonlinear friction ; parameter selection ; servo system
• 刊名：Journal of Systems Science and Complexity
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：29
• 期：1
• 页码：74-98
• 全文大小：947 KB
• 参考文献：[1]Brandenburg G, Bruckl S, Dormann J, et al., Comparative investigation of rotary and linear motor feed drive systems for high precision machine tools, International Workshop on Advanced Motion Control, 2000, 384–389.
  [2]Seamus G and Michael T H, Development of a high-speed CNC cutting machine using linear motors, Journal of Materials Processing Technology, 2005, 166(3): 321–329.CrossRef
  [3]Lin F J, Shyu K K, and Lin C H, Incremental motion control of linear synchronous motor, IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(3): 1011–1022.CrossRef
  [4]Chong G and Li Y, PID control system analysis, design, and technology, IEEE Transactions Conontrol Systems Technology, 2005, 13(4): 559–576.CrossRef
  [5]Narendra and Kumpati S, Robust adaptive control, American Control Conference, 1984.
  [6]Bristow D, Tharayil M, and Alleyne A G, A survey of iterative learning control, IEEE Conontrol Systems Magazine, 2006, 26(3): 96–114.CrossRef
  [7]Guo B and Zhao Z, On convergence of the nonlinear active disturbance rejection control for mimo systems, SIAM J. Control and Optimization, 2013, 51(2): 1727–1757.CrossRef MathSciNet MATH
  [8]Zheng Q, Chen Z Z, and Gao Z Q, A practical approach to disturbance decoupling control, Control Engineering Practice, 2009, 17(9): 1016–1025.CrossRef
  [9]Xue W C and Huang Y, On performance analysis of ADRC for nonlinear uncertain systems with unknown dynamics and discontinuous disturbances, 2013 Chinese Control Conference, 2013, 1102–1107.
  [10]Dong J Y and Li D H, Active disturbance rejection control for complex dynamical systems, System Science and Mathematic, 2013, 33(6): 639–652 (in Chinese).MathSciNet MATH
  [11]Jiang Z, Active disturbance rejection control for the yaw tracking for helicopter, System Science and Mathematic, 2012, 32(6): 641—652 (in Chinese).MATH
  [12]Zheng Q, Gao L Q, and Gao Z, On validation of extended state observer through analysis and experimentation, Journal of Dynamic Systems Measurement & Control, 2012, 134(2): 224–240.CrossRef
  [13]Xiao Y and Zhu K Y, Optimal synchronization control of highprecision motion systems, IEEE Transactions on Industrial Electronics, 2006, 53(4): 1160–1169.CrossRef
  [14]Canudas-De-Wit C, Olsson H, Astrom K J, et al., A new model for control of systems with friction, IEEE Transactions on Automatic Control, 1995, 40(3): 419–425.CrossRef MathSciNet MATH
  [15]Tan K K, Huang S N, and Lee T H, Robust adaptive numerical compensation for friction and force ripple in permanent-magnet linear motors, IEEE Transactions on Magnetics, 2002, 38(1): 221–228.CrossRef MathSciNet
  [16]Han J Q, Auto-disturbances-rejection controller and its application, Control and Decision, 1998, 13(1): 19–23.
  [17]Gao Z Q, Haung Y, and Han J Q, An alternative paradigm for control system design, IEEE Conference on Decision and Control, 2001, 5: 4578–4585.
  [18]Xue W C, Theoretical analysis of active disturbance rejection control, Ph.D. Thesis, 2012.
  [19]Hu T, Xue W C, and Huang Y, Active disturbance rejection control for permanent magnet linear motor, Proceedings of the 31st Chinese Control Conference, 2012, 296–301.
  [20]Castelino K, D’Souza R, and Wright P K, Tool path optimization for minimizing airtime during machining, Journal of Manufacturing Systems, 2003, 22(3): 173–180.CrossRef
  [21]Guo J X, Zhang Q, Gao X S, et al., Time optimal feedrate generation with confined tracking error based on linear programming, Journal of Systems Science and Complexity, 2015, 28(1): 80–95.CrossRef MathSciNet
  [22]Zhang K, Gao X S, Li H, and Yuan C M, A greedy algorithm for feed-rate planning of CNC machines along curved tool paths with confined jerk for each axis, Robotics and computer Integrated Manufacturing, 2012, 28: 472–483.CrossRef
  [23]Fan W, Gao X S, Yan W, et al., Interpolation of parametric CNC machining path under confined jounce, The International Journal of Advanced Manufacturing Technology, 2012, 62(5–8): 719–739.CrossRef
  [24]Zhao C and Huang Y, ADRC bsed input disturbance rejection for minimum-phase plants with unknown orders and/or uncertain relative degrees, Journal of Systems Science and Complexity, 2012, 25(4): 625–640.CrossRef MathSciNet MATH
  [25]Yau H T, Lin M T, and Tsai M S, Real-time NURBS interpolation using FPGA for high speed motion control, Computer-Aided Design, 2006, 38: 1123–1133.CrossRef
  [26]Erkorkmaz K and Altintas Y, High speed CNC system design Part I: Jerk limited trajectory generation and quintic spline interpolation, International Journal of Machine Tools and Manufacture, 2001, 41: 1323–1345.CrossRef
  [27]Altintas Y and Erkorkmaz K, Feedrate optimization for spline interpolation in high speed machine tools, CIRP Annals—Manufacturing Technology, 2003, 52(1): 297–302.CrossRef
  
• 作者单位：Jianxin Guo (1) (2)
  Wenchao Xue (1) (2)
  Tao Hu (1) (2)
  
  1. Key Laboratory of Mathematics Mechanization, Academy of Mathematic and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
  2. Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
  
• 刊物类别：Mathematics and Statistics
• 刊物主题：Systems Theory and Control
  Applied Mathematics and Computational Methods of Engineering
  Operations Research/Decision Theory
  Probability Theory and Stochastic Processes
  
• 出版者：Academy of Mathematics and Systems Science, Chinese Academy of Sciences, co-published with Springer
• ISSN：1559-7067

文摘

Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine. In this paper, based on the principle of Active Disturbance Rejection Control (ADRC), a control method is proposed, where both the extended state observer (ESO) and the reduced order extended state observer (RESO) are used to estimate and compensate for the disturbance. The authors prove that both approaches ensure high accuracy in theory, and give the criterion for parameters selection. The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error. The simulation results on CNC machine show the effectiveness and feasibility of our control approaches. Keywords Active disturbance rejection control CNC machine nonlinear friction parameter selection servo system