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Precision position control of servo systems using adaptive back-stepping and recurrent fuzzy neural networks

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Abstract

To improve position tracking performance of servo systems, a position tracking control using adaptive back-stepping control(ABSC) scheme and recurrent fuzzy neural networks(RFNN) is proposed. An adaptive rule of the ABSC based on system dynamics and dynamic friction model is also suggested to compensate nonlinear dynamic friction characteristics. However, it is difficult to reduce the position tracking error of servo systems by using only the ABSC scheme because of the system uncertainties which cannot be exactly identified during the modeling of servo systems. Therefore, in order to overcome system uncertainties and then to improve position tracking performance of servo systems, the RFNN technique is additionally applied to the servo system. The feasibility of the proposed control scheme for a servo system is validated through experiments. Experimental results show that the servo system with ABS controller based on the dual friction observer and RFNN including the reconstruction error estimator can achieve desired tracking performance and robustness.

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Authors and Affiliations

  1. School of Mechanical Engineering and RIMT, Pusan National University, Busan, 609-735, Korea

    Han Me Kim & Jong Shik Kim

  2. Department of Electrical Engineering, Dong-A University, Busan, 604-714, Korea

    Seong Ik Han

Authors
  1. Han Me Kim
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  2. Seong Ik Han
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  3. Jong Shik Kim
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Corresponding author

Correspondence to Jong Shik Kim.

Additional information

This paper was recommended for publication in revised form by Associate Editor Hyoun Jin Kim

Han Me Kim received the B.S. in Mechanical Design Engineering from Kyeongsang National University in 1999. He received the M.S. in Mechanical and Intelligent Systems Engineering from Pusan National University, Busan, Korea, in 2002. He is currently a Ph. D. candidate at the graduate school of Mechanical Engineering at Pusan National University, Busan, Korea. His research interests include artificial intelligent control, nonlinear control, and friction control.

Seong Ik Han received the B.S. and M. S. in Mechanical Engineering and the Ph. D. in Mechanical Design Engineering from Pusan National Universityin 1987, 1989, and 1995, respectively. From 1995 to 2009, he was An Associate Professor of the Electrical Automation of the Suncheon First College, Suncheon, Korea. He is currently A Research Professor in the Department of Electrical Engineering, Dong-A University, Busan, Korea. His research interests include fuzzy neural networks, nonlinear adaptive control, robotic system control, and friction control.

Jong Shik Kim received the B.S. in Mechanical Design and Production Engineering from Seoul National University in 1977. He received the M.S. in Mechanical Engineering from Korea Advanced Institute of Science and Technonlogy in 1979 and the Ph.D. in Mechanical Engineering from MIT in 1987. He is a professor in the School of Mechanical Engineering, Pusan National University, Korea. His research interests include dynamics and control of vehicle systems and nonlinear control.

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Kim, H.M., Han, S.I. & Kim, J.S. Precision position control of servo systems using adaptive back-stepping and recurrent fuzzy neural networks. J Mech Sci Technol 23, 3059–3070 (2009). https://doi.org/10.1007/s12206-009-0907-1

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  • DOI: https://doi.org/10.1007/s12206-009-0907-1

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