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On-Line Hybrid Intelligent Tracking Control for a Class of Nonaffine Multivariable Systems

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Abstract

A novel B-spline neural backstepping controller design with mean-value approximation and first-order filters is proposed for a class of uncertain multiple-input–multiple-output nonaffine nonlinear systems. By combining the proposed systematic backstepping design technique with B-spline neural network structure, one not only has the improved tracking performance but also reduces the computation time. Moreover, using the proposed control scheme, the problems of higher-order derivative and complexity explosion can be solved. According to the stability analysis, it is proven that the tracking errors can be made small by tuning adjustable parameters appropriately. Finally, simulation results are provided to confirm the effectiveness and applicability of the proposed control scheme.

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Acknowledgments

This work was supported by the National Science Council, Taiwan, under Grants 102-2221-E-003-009, and the “Aim for the Top University Plan 103J1A12” from National Taiwan Normal University and the Ministry of Education, Taiwan.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Taiwan Normal University, 162, Heping East Road, Section 1, Taipei, 106, Taiwan, ROC

    Yi-Hsing Chien, Wei-Yen Wang & Yih-Guang Leu

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  1. Yi-Hsing Chien
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  2. Wei-Yen Wang
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  3. Yih-Guang Leu
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Correspondence to Wei-Yen Wang.

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Chien, YH., Wang, WY. & Leu, YG. On-Line Hybrid Intelligent Tracking Control for a Class of Nonaffine Multivariable Systems. Int. J. Fuzzy Syst. 17, 39–52 (2015). https://doi.org/10.1007/s40815-015-0002-y

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  • DOI: https://doi.org/10.1007/s40815-015-0002-y

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