Paper Title:
The Design of Ship Course Intelligent Controller Based on Adaptive Neural Fuzzy Interference System
  Abstract

Under the condition that the nonlinearity of ship steering model is considered and the assumption that the parameters of the model are uncertain, we proposed an adaptive control algorithm for ship course nonlinear system by incorporating the technique of neural network and fuzzy logic system. In the paper, we presented the structure and characteristics of Adaptive Neuro-Fuzzy Interference System (ANFIS), established the ship course controller, and realized an online learning algorithm to do online parameter estimation. We utilize fuzzy logic to solve the uncertainty problem of control system, neural network to optimize the controller parameters. To demonstrate the applicability of the proposed method, simulation results are presented at the end of this paper. The experiment shows that the ANFIS controller can achieve high performance control under parameter perturbation and other disturbances.

  Info
Periodical
Chapter
Chapter 7: Mechanical & Automation
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
1037-1043
DOI
10.4028/www.scientific.net/AMM.135-136.1037
Citation
G. S. Hu, H. R. Xiao, "The Design of Ship Course Intelligent Controller Based on Adaptive Neural Fuzzy Interference System", Applied Mechanics and Materials, Vols. 135-136, pp. 1037-1043, 2012
Online since
October 2011
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Price
$32.00
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