Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System

Shenglin Mu, Satoru Shibata, Tomonori Yamamoto, Seigo Goto, Shota Nakashima, Kanya Tanaka

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Based on the scheme of predictive fuzzy control combined with neural network (NN) for pneumatic servo system, the learning of NN using Particle Swarm Optimization (PSO) is studied according to experimental investigation in this research. A group of positioning experiments using existent pneumatic servo system were designed to confirm the effectiveness and efficiency of the NN’s learning employing PSO in the imaginary plant construction for the pneumatic system in predictive fuzzy control. The analysis in the study was implemented comparing the results of traditional back-propagation (BP) type NN and the PSO type NN.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages323-332
Number of pages10
DOIs
Publication statusPublished - 1 Jan 2020

Publication series

NameStudies in Computational Intelligence
Volume810
ISSN (Print)1860-949X

Fingerprint

Servomechanisms
Pneumatics
Particle swarm optimization (PSO)
Neural networks
Fuzzy control
Backpropagation
Experiments

Keywords

  • Neural network
  • Particle swarm optimization
  • Pneumatic servo system
  • Position control
  • Predictive fuzzy control

Cite this

Mu, S., Shibata, S., Yamamoto, T., Goto, S., Nakashima, S., & Tanaka, K. (2020). Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. In Studies in Computational Intelligence (pp. 323-332). (Studies in Computational Intelligence; Vol. 810). Springer Verlag. https://doi.org/10.1007/978-3-030-04946-1_32
Mu, Shenglin ; Shibata, Satoru ; Yamamoto, Tomonori ; Goto, Seigo ; Nakashima, Shota ; Tanaka, Kanya. / Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. Studies in Computational Intelligence. Springer Verlag, 2020. pp. 323-332 (Studies in Computational Intelligence).
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Mu, S, Shibata, S, Yamamoto, T, Goto, S, Nakashima, S & Tanaka, K 2020, Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. in Studies in Computational Intelligence. Studies in Computational Intelligence, vol. 810, Springer Verlag, pp. 323-332. https://doi.org/10.1007/978-3-030-04946-1_32

Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. / Mu, Shenglin; Shibata, Satoru; Yamamoto, Tomonori; Goto, Seigo; Nakashima, Shota; Tanaka, Kanya.

Studies in Computational Intelligence. Springer Verlag, 2020. p. 323-332 (Studies in Computational Intelligence; Vol. 810).

Research output: Chapter in Book/Report/Conference proceedingChapter

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Mu S, Shibata S, Yamamoto T, Goto S, Nakashima S, Tanaka K. Experimental Study on Learning of Neural Network Using Particle Swarm Optimization in Predictive Fuzzy for Pneumatic Servo System. In Studies in Computational Intelligence. Springer Verlag. 2020. p. 323-332. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-030-04946-1_32