SELF-TUNING FUZZY SPEED CONTROLLER OF TRAVELLING WAVE ULTRASONIC MOTOR

Publications

Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

GET ALERTS

eISSN: 1178-5608

DESCRIPTION

1
Reader(s)
1
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 7 , ISSUE 1 (March 2014) > List of articles

SELF-TUNING FUZZY SPEED CONTROLLER OF TRAVELLING WAVE ULTRASONIC MOTOR

Jingzhuo Shi * / Juanping Zhao * / Zhe Cao / Yunpeng Liang / Lan Yuan / Bin Sun

Keywords : ultrasonic motor, speed control, fuzzy, ant colony optimization

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 1, Pages 301-320, DOI: https://doi.org/10.21307/ijssis-2017-657

License : (CC BY-NC-ND 4.0)

Received Date : 15-October-2013 / Accepted: 01-February-2014 / Published Online: 27-December-2017

ARTICLE

ABSTRACT

Aiming at the nonlinear characteristic of ultrasonic motor, some control strategies have been proposed to control the rotating speed of ultrasonic motor. But most of these strategies are too complex to realize using a low-cost embedded device. In this paper, a simple fuzzy speed controller is designed for ultrasonic motor. Until now, there has no mature and theoretic design method of fuzzy controller.
Therefore, experience of expert is often used as the base of design. It makes the design of fuzzy controller become a sophisticated task. In this paper, the design method of fuzzy controller based on fuzzy model is described in detail. Rules of the fuzzy controller are optimized offline using ant colony optimization, and the appropriate parameters of fuzzy controller are also ascertained during the process
of optimization. The designed controller is used to control the rotating speed of traveling wave ultrasonic motor with the type of USR60. According to the difference between the actual responses with different speed references, a kind of online tuning method is proposed to modulate the proportional coefficient of fuzzy control. Experiments indicate the validity of the proposed fuzzy controller.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

[1] Zhu H., Li Z. R. and Zhao C. S., “An efficient approach to optimize the vibration mode of bar-type ultrasonic motors”, Ultrasonics, vol.50, 4-5, pp. 491-495, 2010.
[2] Radi B. and Hami A. E., “The study of the dynamic contact in ultrasonic motor”, Applied Mathematical Modelling, vol. 34, No. 12, 2010, pp. 3767-3777.
[3] Puu-An J. and Ching-Chih T., “Equivalent circuit modeling of an asymmetric disc-type ultrasonic motor”, IEEE Transactions on Instrument and Measurement, vol. 58, No. 7, 2009, pp.2351-2357.
[4] Pirrotta S., Sinatra R. and Meschini A., “Evaluation of the effect of preload force on resonance frequencies for a traveling wave ultrasonic motor”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 53, No. 4, 2006, pp. 746-753.
[5] Faa-Jeng L., Ying-Chih H. and Syuan-Yi C., “Field-programmable gate array-based intelligent dynamic sliding-mode control using recurrent wavelet neural network for linear ultrasonic motor”, IET Control Theory Appl., vol. 4, No. 9, 2010, pp. 1511-1532.
[6] Faa-Jeng L., Kung Y.-S., Syuan-Yi C. and Liu, Y.-H., “Recurrent wavelet-based Elman neural network control for multi-axis motion control stage using linear ultrasonic motors”, IET Electr. Power Appl., vol. 4, No. 5, 2010, pp. 314-332.
[7] Faa-Jeng L., Ying-Chih H. and Syuan-Yi C., “FPGA-based computed force control system using Elman neural network for linear ultrasonic motor”, IEEE Transactions on Industrial Electronics, vol. 56, No. 4, 2009, pp. 1238-1253.
[8] Fu P., Guo J. F. and Ding J., “A neuron adaptive PID speed and position control for ultrasonic motors”, Transaction of China Electrotechnical Society, vol. 22, No. 2, 2007, pp. 28-33.
[9] Senjyu T., Kashiwagi T. and Uezato K., “Position control of ultrasonic motors using MRAC and dead-zone compensation with fuzzy inference”, IEEE Transactions on Power Electronics, vol.
17, No. 2, 2002, pp. 265-272.[10] Yoshida T., Senjyu T. and Nakamura M., “Position control of ultrasonic motors using deadzone
compensation with fuzzy neural network”, Electric Power Components and Systems, vol.34, No. 8, 2006, pp. 1253-1266.
[11] Chen T. C., Yu C. H., Chen C. J. and Tsai M. C., “Neuro-fuzzy speed control of travelingwave type ultrasonic motor drive using frequency and phase modulation”, ISA Transactions, vol.47, No. 2, 2008, pp. 325-338.
[12] Faa-Jeng L., Syuan-Yi C. and Po-Huan C., “Interval type-2 fuzzy neural network control for X-Y-Theta motion control stage using linear ultrasonic motors”, Neurocomputing, vol.72, 4-6, 2009, pp. 1138-1151.
[13] Amir Mehdi Yazdani, Ahmadreza Ahmadi, Salinda Buyamin, Mohd Fua’ad Rahmat, Farshad Davoudifar and Herlina Abd Rahim, “Imperialist competitive algorithm-based fuzzy PID control methodology for speed tracking enhancement of stepper motor”, International Journal on Smart Sensing and Intelligent Systems, vol. 5, No. 3, 2012, pp. 717-741.
[14] Zulfatman and M. F. Rahmat, “Application of self-Tuning fuzzy PID controller on industrial hydraulic actuator using system identification approach”, International Journal on Smart Sensing and Intelligent Systems, vol. 2, No. 2, 2009, pp. 246-261.
[15] Zu-Qiang Long, Yue-Bing Xu, Can Liu, “Fuzzy Control Algorithm Based on Variable Universe of Discourse and Its Expansion-Contraction Factors”, Joumal of Convergence Information Technology, vol. 7, No. 19, 2012, pp. 570-577.
[16] Zuqiang Long, Wen Long, Yan Yuan, Xiaobo Yi, “Design of Backing-up fuzzy controllers based on variable universe of discourse”, International Journal on Smart Sensing and Intelligent Systems, vol. 6, No. 2, 2013, pp. 505-522.
[17] Shi J., Lv L. and Zhang Y., “Dynamic Takagi-Sugeno Model for the Control of Ultrasonic Motor”, Journal of Control Science and Engineering, 2011(2011), 2011, pp.1-9.

EXTRA FILES

COMMENTS