Abstract
This paper addresses the development of a new control strategy to regulate cutting force in a high-speed machining process. Fuzzy basis functions (FBF), on the basis of L.X.Wang’s approach, serve as basement for designing and implementing adaptive fuzzy control system in an open computerized numerical control (CNC). The controller uses cutting force measured from a dynamometric platform, and mathematically processed by means of an integrated application, to perform real-time modification of feed rate. The integration process, design steps and results of applying the adaptive fuzzy-control system in actual high-speed machining operations corroborate the suitability of the proposed control strategy for real-time applications. Moreover, the results show a good transient response in the cutting force pattern despite the complexity of the mechanized part.
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References
Landers, R.G., Ulsoy, A.G., Ma, Y.-H.: A comparison of model-based machining force control approaches. Int. Journal of Machinte Tools and Manufacture 44, 733–748 (2004)
Haber-Guerra, R.E.: Preliminary results in high speed machining control and monitoring. A personal perspective, School of Mechanical Engineering, Georgia Institute of Technology, July 7 (2004), Summary: http://pmrc.marc.gatech.edu/fmpr/PMRCSeminars.html
Haber-Guerra, R.E., Alique, J.R., Alique, A., Haber-Haber, R.: Controlling a complex electromechanical process on the basis of a neurofuzzy approach, Future Generation of Computer Systems (2004) (doi:10.1016/j.future.2004.03.001)
Haber-Guerra, R.E., Alique, J.R.: Nonlinear internal model control using neural networks: Applications to machining processes. Neural Computing and Applications 13, 47–55 (2004)
Liu, Y., Zhuo, L., Wang, C.: Intelligent adaptive control in milling process. International Journal of Computer Integrated Manufacturing 12(5), 453–460 (1999)
Wang, L.X.: Stable adaptive fuzzy controllers with application to inverted pendulum tracking. IEEE Transaction on Systems, Man, and Cybernetics, 667–691 (1996)
Wang, L.X.: Automatic design of fuzzy controllers. Automatica 35(8), 1471–1475 (1999)
Haber-Guerra, R.E., Jiménez, J.E., Coronado, J.L., Jiménez, A.: Cutting force model for high speed machining processes. Revista Metalurgia Madrid 40(4), 247–258 (2004)
Haber-Guerra, R.E., Jiménez, J.E., Peres, C.R., Alique, J.R.: An investigation of tool wear monitoring in a high-speed machining process. Sensors and Actuators A: Physics 116, 539–545 (2004)
Rober, S.J., Shin, Y.C., Nwokah, O.D.I.: A digital robust controller for cutting force control in the end milling process. Journal of Dynamic Systems, Measurement and Control 119, 146–152 (1997)
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Haber-Guerra, R., Haber-Haber, R., Alique, J.R. (2005). Controlling Force Based on Radial Fuzzy Functions in High-Speed Machining Processes. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_151
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DOI: https://doi.org/10.1007/11494669_151
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26208-4
Online ISBN: 978-3-540-32106-4
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