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Output Feedback Adaptive Robust NN Control for a Class of Nonlinear Discrete-Time Systems

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Advances in Neural Networks – ISNN 2013 (ISNN 2013)

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Abstract

In this paper, output feedback direct adaptive robust NN control is investigated for a class of nonlinear discrete-time systems in strict-feedback form. To construct output feedback control, the original strict-feedback system is transformed into a cascade form, which the output feedback of the nonlinear discrete-time system can be carried out. Then with employment of the inputs and outputs, the output feedback direct adaptive robust NN control is developed. The HONNs is exploited to approximate unknown function, and a stable adaptive NN controller is synthesized. The proposed algorithm improves the rubostness of the discrete-time nonlinear systems. It is proven that all the signals in closed-loop system are uniformly ultimately bounded (UUB). A simulation example is presented to illustrate the effectiveness of the proposed algorithm.

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Wang, X., Li, T., Fang, L., Lin, B. (2013). Output Feedback Adaptive Robust NN Control for a Class of Nonlinear Discrete-Time Systems. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_27

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  • DOI: https://doi.org/10.1007/978-3-642-39068-5_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39067-8

  • Online ISBN: 978-3-642-39068-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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