JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (2): 28-33.

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Adaptive behavior design based on FNN for the mobile robot

LI Yi-bin1, LI Cai-hong1,2, SONG Yong1   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, China;
    2. School of Computer Science and Technology, Shandong University of Technology, Zibo 255049, China
  • Received:2009-09-10 Online:2010-04-16 Published:2009-09-10

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Abstract:

The fuzzy neural network (FNN) controller was formed by combining the fuzzy control and the neural networks. The fuzzy rules were collected automatically by reinforcement Q-Learning (QL) on-line beforehand. The rules were  implicitly stored in the FNN after the off-line training. In control applications, the complex search and inference of the rules were unnecessary, and the best adaptive behavior could be produced in the output without looking up the table. The simulation results show that because all training samples are from the trained fuzzy rules, the output is almost the same as the result of the training rules.
 

Key words: mobile robot, fuzzy neural network, adaptive behavior; , fuzzy control rules

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