• Electronics Optics & Control
  • Vol. 28, Issue 8, 1 (2021)
WANG Suzhen and LIU Jianfeng
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2021.08.001 Cite this Article
    WANG Suzhen, LIU Jianfeng. Multi-model Adaptive Control of Nonlinear Systems Based on Improved BP Neural Network[J]. Electronics Optics & Control, 2021, 28(8): 1 Copy Citation Text show less

    Abstract

    As for a class of nonlinear discrete systems with unknown parametersa multi-model control method based on the improved BP neural network is proposed.Firstlythe nonlinear system is expressed with a linear part and a nonlinear part.When the nonlinear part has small impact on the systemthe linear robust controller designed based on the fixed model and the adaptive model is directly used to control the system.When the nonlinear part has large impact on the systemthe adaptive control under the improved BP neural network is adopted.Secondlythe switching criterion is used to smoothly switch the control input and the stability of the system is proved.Finallysimulation results show that the proposed method can improve the system control quality and reduce the oscillation of the control signal.
    WANG Suzhen, LIU Jianfeng. Multi-model Adaptive Control of Nonlinear Systems Based on Improved BP Neural Network[J]. Electronics Optics & Control, 2021, 28(8): 1
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