Parameters Turning of the Active-Disturbance Rejection Controller Based on RBF Neural Network - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

Parameters Turning of the Active-Disturbance Rejection Controller Based on RBF Neural Network

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Baifen Liu
  • Function : Author
  • PersonId : 1013088
Ying Gao
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  • PersonId : 1013089

Abstract

The Active-disturbance rejection control (ADRC) has the advantage of strong robustness, anti-interference capability, and it does not rely on the accurate math model of controlled plant. But the parameter self-turning of ADRC isn’t as easy as PID controller because there are more parameters to turn in ADRC. In this paper the parameters are self-turning by the Radial Basis Function (RBF) Neural Network. The results of the simulation indicate that the controller has good anti-interference capability and fast response. The robustness of the system is improved.
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Dates and versions

hal-01564845 , version 1 (19-07-2017)

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Attribution - CC BY 4.0

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Baifen Liu, Ying Gao. Parameters Turning of the Active-Disturbance Rejection Controller Based on RBF Neural Network. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.260-267, ⟨10.1007/978-3-642-18369-0_30⟩. ⟨hal-01564845⟩
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