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Adaptive backstepping control for flexible-joint manipulator using interval type-2 fuzzy neural network approximator

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Abstract

In this paper, an adaptive backstepping controller based on interval type-2 fuzzy neural network (IT2FNN) approximator is proposed for flexible-joint manipulator with mismatched uncertainties. Backstepping control has the ability to deal with the mismatched problem, and IT2FNN approximator can be utilized to approximate unknown nonlinear functions. Through the Lyapunov stability analysis, all the signals in the closed-loop system are guaranteed to be ultimately bounded. Simulation results show that the tracking error of the proposed controller can be reduced to arbitrarily small values, and the tracking performance is better than the adaptive backstepping controllers based on type-1 fuzzy neural network approximator and neural network approximator.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (61703291) and the Applied Basic Research Program of Science and Technology Department of Sichuan Province, China (2016JY0085).

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Authors and Affiliations

  1. College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, China

    Songyi Dian, Yi Hu, Tao Zhao & Jixia Han

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  1. Songyi Dian
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Correspondence to Tao Zhao.

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Dian, S., Hu, Y., Zhao, T. et al. Adaptive backstepping control for flexible-joint manipulator using interval type-2 fuzzy neural network approximator. Nonlinear Dyn 97, 1567–1580 (2019). https://doi.org/10.1007/s11071-019-05073-8

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  • DOI: https://doi.org/10.1007/s11071-019-05073-8

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