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Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks

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Abstract

In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control (ABFCNC) system for motion/force control of the mobile-manipulator robot (MMR) is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results.

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Author information

Authors and Affiliations

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

    Thang-Long Mai & Yaonan Wang

  2. Faculty of Electronics Engineering, Industrial University of Hochiminh City, Hochiminh City, Vietnam

    Thang-Long Mai

Authors
  1. Thang-Long Mai
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  2. Yaonan Wang
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Corresponding author

Correspondence to Thang-Long Mai.

Additional information

This work was supported by the National Natural Science Foundation of China (Nos. 6117075, 60835004) and the National High Technology Research and Development Program of China (863 Program) (Nos. 2012AA111004, 2012AA112312).

Thang-Long MAI received the B.Sc. and M.Sc. degrees from Department of Automatic Control, Faculty of Electrical and Electronics, Viet Nam National University, Ho Chi Minh City University of Technology. He received the Ph.D. degree at College of Electrical and Information, Hunan University, China. His current research interests include robotic control, learning control and intelligent control.

Yaonan WANG received the B.Sc. degree in Computer Engineering from East China Science and Technology University (ECSTU), Fuzhou, China, in 1981, and the M.Sc. and Ph.D. degrees in Electrical Engineering from Hunan University, Changsha, China, in 1989 and 1995, respectively. From 1995 to 1997, he was a postdoctoral research fellow with the National University of Defense 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 are intelligent control and information processing, robot control, image processing, and industrial process contro.

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Mai, TL., Wang, Y. Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks. Control Theory Technol. 12, 368–382 (2014). https://doi.org/10.1007/s11768-014-3181-4

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  • DOI: https://doi.org/10.1007/s11768-014-3181-4

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