Scholars@Duke

Memristive radial basis function neural network for parameters adjustment of PID controller

Publication ,  Conference
Li, X; Duan, S; Wang, L; Huang, T; Chen, Y
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2014
Published version (DOI)

Radial basis function (RBF) based-identification proportional– integral–derivative (PID) can automatically adjust the parameters of PID controller with strong self-organization, self-learning and self-adaptive ability. However, the compound controller has complex weight updating algorithm and large calculation. Memristor, applied well to the investigation of storage circuit and artificial intelligence, is a nonlinear element with memory function. Thus, it can be introduced to RBF neural network as electronic synapse to save and update the synaptic weights. This paper builds a model of memristive RBF-PID (MRBF-PID), and proposes the updating algorithm of weight upon memristance. The proposed MRBF-PID is used for the control of a nonlinear system. Its controlling effect is showed by numerical simulation experiment.

Duke Scholars

Yiran Chen
Author Yiran Chen Electrical and Computer Engineering

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

10.1007/978-3-319-12436-0_17

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2014

Volume

8866

Start / End Page

150 / 158

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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ICMJE
MLA
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Li, X., Duan, S., Wang, L., Huang, T., & Chen, Y. (2014). Memristive radial basis function neural network for parameters adjustment of PID controller. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8866, pp. 150–158). https://doi.org/10.1007/978-3-319-12436-0_17
Li, X., S. Duan, L. Wang, T. Huang, and Y. Chen. “Memristive radial basis function neural network for parameters adjustment of PID controller.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8866:150–58, 2014. https://doi.org/10.1007/978-3-319-12436-0_17.
Li X, Duan S, Wang L, Huang T, Chen Y. Memristive radial basis function neural network for parameters adjustment of PID controller. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014. p. 150–8.
Li, X., et al. “Memristive radial basis function neural network for parameters adjustment of PID controller.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8866, 2014, pp. 150–58. Scopus, doi:10.1007/978-3-319-12436-0_17.
Li X, Duan S, Wang L, Huang T, Chen Y. Memristive radial basis function neural network for parameters adjustment of PID controller. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2014. p. 150–158.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

10.1007/978-3-319-12436-0_17

EISSN

1611-3349

ISSN

0302-9743

Publication Date

January 1, 2014

Volume

8866

Start / End Page

150 / 158

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences