Control of a mobile robot using generalized dynamic fuzzy neural networks
作者： M.J. Er , Tien Peng Tan , Sin Yee Loh
DOI: 10.1016/J.MICPRO.2004.04.002
关键词:
摘要: Abstract This paper presents the design and implementation of a neural fuzzy controller suitable for real-time control an autonomous mobile robot. The is developed based on Generalized Dynamic Fuzzy Neural Networks (GDFNN) learning algorithm Wu et al. (IEEE Transactions System 9 (4), 2001, 578–594). Not only parameters can be optimized, but also structure self-adaptive. Experimental results show that in comparison with conventional fuzzy-logic-based controller, proposed superior performance.
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sci-hub.se 参考文章(3)
Edoardo Franzi, Paolo Ienne, None, Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms international symposium on experimental robotics. pp. 501- 513 ,(1993) , 10.1007/BFB0027617
Tomohiro Takagi, Michio Sugeno, Fuzzy identification of systems and its applications to modeling and control systems man and cybernetics. ,vol. 15, pp. 116- 132 ,(1985) , 10.1109/TSMC.1985.6313399
Shiqian Wu, Meng Joo Er, Yang Gao, A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks IEEE Transactions on Fuzzy Systems. ,vol. 9, pp. 578- 594 ,(2001) , 10.1109/91.940970