DocumentCode :
2752112
Title :
PSO training of the Neural Network application for a controller of the line tracing car
Author :
Hoshino, Yukinobu ; Takimoto, Hiroshi
Author_Institution :
Dept. of Electron. & Photonic Syst. Eng., Kochi Univ. of Technol., Kami, Japan
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
In this research, a fuzzy controller system is useful as a key technique to design a machine controller because a fuzzy system can be designed by fuzzy sets, which can be represented using linguistic descriptions of natural language. Those natural languages are able capture human knowledge in fuzzy rules. A fuzzy controller system consists of fuzzy rules and involved techniques. Recently, the research of the fuzzy control has controlled various machines. We verified that fuzzy control can be applicable to a line tracing car control, which is running at a high speed. In our research, designers took a huge amount of time to adjust and setup the fuzzy controller. In order to apply the Neural Network (NN) controller, we designed a simple network system, and setup a PSO_VC and parameters. The PSO_VC (a PSO with Velocity Control) is a speed control strategy for all moving particles on the PSO. In order to configure the NN, a very powerful and quick PSO_VC is used. The PSO_VC is able to adjust all weights and threshold levels. In this paper we present the performances of accurate control and compare results between fuzzy controller and the NN controller.
Keywords :
angular velocity control; automobiles; fuzzy control; fuzzy set theory; natural languages; neurocontrollers; particle swarm optimisation; PSO training; PSO-VC; fuzzy controller system; fuzzy rules; fuzzy sets; human knowledge; line tracing car controller; linguistic descriptions; machine controller design; moving particles; natural language; neural network application; simple network system; speed control strategy; threshold levels; Artificial neural networks; DC motors; Fuzzy control; Sensors; Training; Velocity control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
ISSN :
1098-7584
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2012.6251141
Filename :
6251141
Link To Document :
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