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Robust dynamic surface control of flexible joint robots using recurrent neural networks

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Abstract

A robust neuro-adaptive controller for uncertain flexible joint robots is presented. This control scheme integrates H-infinity disturbance attenuation design and recurrent neural network adaptive control technique into the dynamic surface control framework. Two recurrent neural networks are used to adaptively learn the uncertain functions in a flexible joint robot. Then, the effects of approximation error and filter error on the tracking performance are attenuated to a prescribed level by the embedded H-infinity controller, so that the desired H-infinity tracking performance can be achieved. Finally, simulation results verify the effectiveness of the proposed control scheme.

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University, Changsha Hunan, 410082, China

    Zhiqiang Miao & Yaonan Wang

Authors
  1. Zhiqiang Miao
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  2. Yaonan Wang
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Corresponding author

Correspondence to Zhiqiang Miao.

Additional information

This work was supported by the National Natural Science Foundation of China (Nos. 60835004, 61175075), and the Hunan Provincial Innovation Foundation for Postgraduate (No. CX2012B147).

Zhiqiang MIAO received his B.S. and M.S. degrees in Electrical and Information Engineering from Hunan University, Changsha, China, in 2010 and 2012, respectively, where he is currently working toward the Ph.D. degree with the College of Electrical and Information Engineering. His research interests include intelligent control theory and application and robot control.

Yaonan WANG received his B.S. degree in Computer Engineering from East China Science and Technology University (ECSTU), Fuzhou, China, in 1981, and M.S. and Ph.D. degrees in Electrical Engineering from Hunan University, Changsha, China, in 1990 and 1994, respectively. From 1994 to 1995, he was a postdoctoral research fellow with the National University of Defence Technology. From 1981 to 1994, he worked with ECSTU. From 1998 to 2000, he was a senior Humboldt fellow in Germany, and from 2001 to 2004, he was a visiting professor with the University of Bremen, Bremen, Germany. He has been a professor at Hunan University since 1995. His research interests include intelligent control and information processing, robot control, industrial process control, and image processing.

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Miao, Z., Wang, Y. Robust dynamic surface control of flexible joint robots using recurrent neural networks. J. Control Theory Appl. 11, 222–229 (2013). https://doi.org/10.1007/s11768-013-1240-x

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  • DOI: https://doi.org/10.1007/s11768-013-1240-x

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