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Adaptive trajectory tracking neural network control with robust compensator for robot manipulators

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Abstract

This paper presents an adaptive trajectory tracking neural network control using radial basis function (RBF) for an n-link robot manipulator with robust compensator to achieve the high-precision position tracking. One of the difficulties in designing a suitable control scheme which can achieve accurate trajectory tracking and good control performance is to guarantee the stability and robustness of control system, due to friction forces, external disturbances error, and parameter variations. To deal with this problem, the RBF network is investigated to the joint position control of an n-link robot manipulator. The RBF network is one approach which has shown a great promise in this sort of problems because of its fast learning algorithm and better approximation capabilities. The adaptive RBF network can effectively improve the control performance against large uncertainty of the system. The adaptive turning laws of network parameters are derived using the back-propagation algorithm and the Lyapunov stability theorem, so that the stability of the entire system and the convergence of the weight adaptation are guaranteed. In this control scheme, a robust compensator plays as an auxiliary controller to guarantee the stability and robustness under various environments such as the mass variation, the external disturbances, and modeling uncertainties. Finally, the simulation and experimental results in comparison with adaptive fuzzy and wavelet network control method are provided to verify the effectiveness of the proposed control methodology.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant No. 61175075) National Hightech Research and Development Projects (Grant Nos. 2012AA112312, 2012AA11004). The authors would like to thank the associate editor and the reviewers for their constructive comments, which greatly improved the quality for this work.

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Authors and Affiliations

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

    Pham Van Cuong & Wang Yao Nan

  2. College of Electrical Technical Technology, Hanoi University of Industry, Hanoi, Vietnam

    Pham Van Cuong

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  1. Pham Van Cuong
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  2. Wang Yao Nan
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Correspondence to Pham Van Cuong.

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Van Cuong, P., Nan, W.Y. Adaptive trajectory tracking neural network control with robust compensator for robot manipulators. Neural Comput & Applic 27, 525–536 (2016). https://doi.org/10.1007/s00521-015-1873-4

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  • DOI: https://doi.org/10.1007/s00521-015-1873-4

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