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author:

Huang, Y. (Huang, Y..) [1] | Wu, D. (Wu, D..) [2]

Indexed by:

Scopus

Abstract:

Extreme learning machine is a novel single hidden layer feedforward neural networks with a strong abilities, for example simple net structure, fast learning speed, good generalization and so on. Aimed at the system with a delay unit, A new control strategy for internal model control is proposed to set up an inverse model of the minimal phase subsystem by using extreme learning machine with in-out system datum. Moreover, the relative stable error for internal model control system with a delay unit is presented to evaluate the system performance. The features for the internal model control system based on extreme learning machine are compared with that based on neural network. The experimental results indicate that the internal model control system based on extreme learning machine has small stable error and strong robustness. © 2011 IEEE.

Keyword:

extreme learning machine; internal model control; inverse model; pure delay; stable error

Community:

  • [ 1 ] [Huang, Y.]School of Electric Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Wu, D.]School of Electric Engineering and Automation, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • [Huang, Y.]School of Electric Engineering and Automation, Fuzhou University, Fuzhou, China

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Source :

2011 International Conference on Electric Information and Control Engineering, ICEICE 2011 - Proceedings

Year: 2011

Page: 2391-2395

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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