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A NN-Based Hybrid Intelligent Algorithm for a Discrete Nonlinear Uncertain Optimal Control Problem

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Abstract

A discrete-time nonlinear optimal control system with uncertain perturbation is studied in this paper. A value-iteration-based hybrid intelligent algorithm (HIA), incorporating heuristic dynamic programming algorithm and uncertain simulation, is presented. And some characters of the HIA are provided. Two neural networks are used in the algorithm: a critic network is aimed at approximating the objective function, as well as an active network is used to obtain an uncertain optimal control law. As an application, a schistosomiasis compartment SI model is solved to illustrate the feasibility and effectiveness of the HIA.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (No. 61273009).

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Authors and Affiliations

  1. School of Science, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, China

    Chunxiao Ding, Yun Sun & Yuanguo Zhu

  2. School of Mathematical Sciences, Liaocheng University, Liaocheng, 252059, Shandong, China

    Chunxiao Ding

Authors
  1. Chunxiao Ding
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  2. Yun Sun
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  3. Yuanguo Zhu
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Correspondence to Yuanguo Zhu.

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Ding, C., Sun, Y. & Zhu, Y. A NN-Based Hybrid Intelligent Algorithm for a Discrete Nonlinear Uncertain Optimal Control Problem. Neural Process Lett 45, 457–473 (2017). https://doi.org/10.1007/s11063-016-9536-8

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