The use of fuzzy chip to implement the control of machining processes is investigated. The hardware solution can process rules in fuzzy controllers at high speed. In this paper, fuzzy-chip-based regular and self-tuning controllers are developed to maintain a constant cutting force during machining processes under time-varying cutting conditions. In the fuzzy-chip-based self-tuning controller, two knowledge bases are employed. One base is used to implement the inference of control rules and the other to execute tuning rules for adjusting the output scaling factor on line. The structure makes the proposed fuzzy-chip-based self-tuning controller different from those fuzzy adaptive controllers developed in machining. Those fuzzy-chip-based controllers are characterized by the simple structure and practical applicability for real-time implementation. Both simulation and experimental results on machining processes show that the fuzzy-chip-based controllers demonstrate feasibility, applicability, and adaptability.
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March 2003
Technical Papers
Fuzzy-Chip-Based Control and Its Application to Adaptive Machining
Xifan Yao, Associate Professor,
Xifan Yao, Associate Professor,
Department of Mechatronic Engineering, South China University of Technology, Guangzhou 510641, China
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Xifan Yao, Associate Professor,
Department of Mechatronic Engineering, South China University of Technology, Guangzhou 510641, China
Contributed by the Dynamic Systems and Control Division of the THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received by the ASME Dynamic Systems and Control Division, February 2000; final revision, August 2002. Associate Editor: R. Langari.
J. Dyn. Sys., Meas., Control. Mar 2003, 125(1): 74-79 (6 pages)
Published Online: March 10, 2003
Article history
Received:
February 1, 2000
Revised:
August 1, 2002
Online:
March 10, 2003
Citation
Yao, X. (March 10, 2003). "Fuzzy-Chip-Based Control and Its Application to Adaptive Machining ." ASME. J. Dyn. Sys., Meas., Control. March 2003; 125(1): 74–79. https://doi.org/10.1115/1.1543156
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