single-au.php

IJAT Vol.12 No.5 pp. 631-641
doi: 10.20965/ijat.2018.p0631
(2018)

Paper:

Adaptive Active Vibration Control for Machine Tools with Highly Position-Dependent Dynamics

Robin Kleinwort, Jonathan Platz, and Michael F. Zaeh

Technical University of Munich
Boltzmannstrasse 15, 85748 Garching, Germany

Corresponding author

Received:
November 29, 2017
Accepted:
June 5, 2018
Published:
September 5, 2018
Keywords:
chatter, vibrations, active damping, adaptive controller
Abstract

The material removal rates of machine tools are often limited by chatter, which is caused by the machine’s most flexible structural modes. Active vibration control systems mitigate chatter vibrations and increase the chatter free axial depth of cut. However, model-based control strategies reach their limit if the machine tool exhibits highly position-dependent dynamics. In this paper, an adaptive control strategy is presented. This strategy uses online system identification to adapt the controller. The adaption algorithm is mainly automated. However, a few parameters still need to be selected. Therefore, a methodology for the determination of the optimal parameters is proposed. The adaptive controller was implemented on a B&R PLC and its suitability was verified experimentally by the observation of notable increases in the chatter-free material removal rates.

Cite this article as:
R. Kleinwort, J. Platz, and M. Zaeh, “Adaptive Active Vibration Control for Machine Tools with Highly Position-Dependent Dynamics,” Int. J. Automation Technol., Vol.12, No.5, pp. 631-641, 2018.
Data files:
References
  1. [1] J. Munoa, X. Beudaert, Z. Dobovari, Y. Altintas, E. Budak, C. Brecher, and G. Stepan, “Chatter Suppression Techniques in Metal Cutting,” CIRP Annals, Vol.65, No.2, pp. 785-808, 2016.
  2. [2] I. Kono, T. Miyamoto, K. Utsumi, K. Nishikawa, H. Onozuka, J. Hirai, and N. Sugita, “Study on Machining Vibration Suppression with Multiple Tuned Mass Dampers: Vibration Control for Long Fin Machining,” Int. J. Automation Technol., Vol.11, No.2, pp. 206-214, 2017.
  3. [3] W. Bickel, K. Litwinski, and B. Denkena, “Increase of Process Stability with Innovative Spindle Drives,” New Production Technologies in Aerospace Industry, pp. 145-151, 2014.
  4. [4] X. Lu, F. Chen, and Y. Altintas, “Magnetic actuator for active damping of boring bars,” CIRP Annals, Vol.63, No.1, pp. 369-372, 2014.
  5. [5] C. Brecher, D. Manoharan, U. Ladra, and H.-G. Köpken, “Chatter suppression with an active workpiece holder,” Production Engineering, Vol.4, No.2-3, pp. 239-245, 2010.
  6. [6] E. Abele, G. Pfeiffer, B. Jalizi, and A. Bretz, “Simulation and development of an active damper with robust μ-control for a machine tool with a gantry portal,” Production Engineering, Vol.10, No.4-5, pp. 519-528, 2016.
  7. [7] J. Munoa, I. Mancisidor, N. Loix, L. G. Uriarte, R. Barcena, and M. Zatarain, “Chatter suppression in ram type travelling column milling machines using a biaxial inertial actuator,” CIRP Annals, Vol.62, No.1, pp. 407-410, 2013.
  8. [8] M. F. Zaeh, R. Kleinwort, P. Fagerer, and Y. Altintas, “Automatic tuning of active vibration control systems using inertial actuators,” CIRP Annals, Vol.66, No.1, pp. 365-368, 2017.
  9. [9] K. Seto, “Active Control: Control Theory as Viewed from Applications,” J. Robot. Mechatron., Vol.6, No.3, pp. 184-190, 1994.
  10. [10] J. Hesselbach, H.-W. Hoffmeister, B.-C. Schuller, and K. Loeis, “Development of an active clamping system for noise and vibration reduction,” CIRP Annals, Vol.59, No.1, pp. 395-398, 2010.
  11. [11] D. G. Ford, A. Myers, F. Haase, S. Lockwood, and A. Longstaff, “Active vibration control for a CNC milling machine,” Proc. of the Institution of Mechanical Engineers, Part C: J. of Mechanical Engineering Science, Vol.228, No.2, pp. 230-245, 2014.
  12. [12] M. F. Zaeh, M. Waibel, and M. Baur, “A Computational Approach to the Integration of Adaptronical Structures in Machine Tools,” Proc. of the Int. Symp. on Computational Structural Engineering, pp. 1017-1028, 2009.
  13. [13] C. Hansen, S. Snyder, X. Qiu, L. Brooks, and D. Moreau, “Active control of noise and vibration,” CRC Press, 1997.
  14. [14] S. M. Kuo and D. R. Morgan, “Active noise control systems: Algorithms and DSP implementations,” Wiley, 1996.
  15. [15] R. J. Allemang, “The Modal Assurance Criterion – Twenty Years of Use and Abuse,” J. of Sound and Vibration, Vol.37, No.8, pp. 14-21, 2003.
  16. [16] M. Kamenetsky and B. Widrow, “A Variable Leaky LMS Adaptive Algorithm,” IEEE Conf. Record of the Thirty-Eighth Asilomar Conf. on Signals, Systems and Computers, pp. 125-128, 2004.
  17. [17] R. H. Kwong and E. W. Johnston, “A Variable Step Size LMS Algorithm,” IEEE Trans. on Signal Processing, Vol.40, No.7, pp. 1633-1642, 1992.
  18. [18] X. Qiu and C. H. Hansen, “A study of time-domain FXLMS algorithms with control output constraint,” The J. of the Acoustical Society of America, Vol.109, No.6, pp. 2815-2823, 2001.
  19. [19] W. S. Gan, S. Mitra, and S. M. Kuo, “Adaptive Feedback Active Noise Control Headset: Implementation, Evaluation and Its Extensions,” IEEE Trans. on Consumer Electronics, Vol.51, No.3, pp. 975-982, 2005.
  20. [20] A. Carini and S. Malatini, “Optimal Variable Step-Size NLMS Algorithms With Auxiliary Noise Power Scheduling for Feedforward Active Noise Control,” IEEE Trans. on Audio, Speech, and Language Processing, Vol.16, No.8, pp. 1383-1395, 2008.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Dec. 11, 2018