IIAE CONFERENCE SYSTEM, The 1st IEEE/IIAE International Conference on Intelligent Systems and Image Processing 2013 (ICISIP2013)

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Real-time Intelligent PID Controller for Ultrasonic Motor
Shenglin Mu, Kanya Tanaka, Shota Nakashima, Djoewahir Alrijadjis

Last modified: 2013-10-01

Abstract


In order to get good performance of ultrasonic motors (USMs) in real applications, a real-time intelligent PID controller is proposed in this paper. To overcome the problems of characteristic variation and nonlinearity, an intelligent PID controller combined with particle swarm optimization (PSO) type neural network (NN) is studied in real-time environment for USM control. In the proposed method, an NN controller is designed for adjusting PID gains. The learning of NN is implemented by PSO updating the weights of NN on-line. By employing the proposed method, the characteristic changes and nonlinearity of USM can be compensated effectively in real-time environment. The effectiveness of the method is confirmed by experiments.

Keywords


ultrasonic motor, PID control, real-time, neural network, particle swarm optimization

References


(1) T. Kenjo and T. Sashida: “An Introduction of Ultrasonic Motor” Oxford Science Publications, 1993.

(2) K. Uchino: “Piezoelectric ultrasonic motors: Overview”, Smart Material Structure, Vol. 7: pp. 273–285, 1998

(3) K. Adachi: “Actuator with friction drive: Ultrasonic motor”, The Japan Society of Mechanical Engineers, Vol. 108: pp. 48-51, 2005

(4) C. Zhao: “Ultrasonic Motor - Technologies and Applications”, Science Press Beijing and Springer-Verlag Berlin Heidelberg, Beijing, 2011

(5) T. Senjyu, H. Miyazato, and K. Uezato: “Position control of ultrasonic motor using neural network” (in Japanese), Transaction of the Institute of Electrical Engineers of Japan D, Vol.116: pp. 1059–1066, 1996

(6) F. Lin, R. Wai, and C. Hong: “Identification and control of rotary traveling-wave type ultrasonic motor using neural networks”, IEEE Transactions on Control Systems Technology, Vol. 9: pp. 672–680, 2001

(7) S. Mu and K. Tanaka: “Intelligent IMC-PID control using PSO for ultrasonic motor”, International Journal of Engineering Innovation and Management, Vol. 1: pp. 69–76, 2011

(8) K. Astrom, T. Hagglund, C. Hang, and W. Ho: “Automatic tuning and adaptation for PID controllers - a survey”, Control Engineering Practice, Vol. 1: pp. 699–714, 1993

(9) S. Mu, K. Tanaka, Y. Wakasa, T. Akashi, N. Kobayashi, S. Uchikado, and Y. Osa: “Intelligent IMC-PID control for ultrasonic motor”, Proceedings of International Conference of Networking, Sensing, and Control, 2009

(10) K. Tanaka, Y. Yoshimura, Y. Wakasa, T. Akashi, M. Oka, and S. Mu: “Variable gain type intelligent PID control for ultrasonic motor” (in Japanese), The Japan Society Applied Electromagnetics and Mechanics, Vol. 17: pp. 107–113, 2009

(11) J. Kennedy and R. Eberhart: “Particle Swarm Optimization”, Proc. IEEE Int. Conf. Neural Networks, Perth, Australia, pp. 1942-1948, 1995

(12)M. Clerc and J. Kennedy: “The Particle Swarm:Explosion, Stability, and Convergence in a Multi-Dimensional Complex Space”, IEEE Trans. Evolutionary Computation, Vol. 6, No. 1, pp.58-73, 2002

(13) J. Kennedy, R. Eberhart: “Swarm Intelligence”, Morgan Kaufmann Publishers, 2001

(14)M. Ito and M. Tanaka: “A Study of Particle Swarm Optimization for Neural Network Training”, A publication of Electronics, Information and System Society, pp. 1087-1089, 2005


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