DocumentCode :
3331308
Title :
T-S adaptive neural network fuzzy control applied in two-wheeled self-balancing robot
Author :
Junfeng Wu ; Shengwei Jia
Author_Institution :
Coll. of Autom., Harbin Univ. of Sci. & Technol., Harbin, China
Volume :
2
fYear :
2011
fDate :
22-24 Aug. 2011
Firstpage :
1023
Lastpage :
1026
Abstract :
This paper regarded Two-wheeled self-balancing robot of Googol Technology Limited as the object of study, corresponding built an exact mathematic model and got system state space equation and its decouple after linearization the model with reasonable methods. At the end, T-S Adaptive neural network fuzzy controller was designed and simulated to obtain the ideal simulation curve. The results show that this adaptive neural network fuzzy controller achieved the desired good results with good dynamic performance and stability.
Keywords :
adaptive control; control system synthesis; fuzzy control; mobile robots; neurocontrollers; stability; Googol Technology Limited; T-S adaptive neural network fuzzy control; mathematic model; stability; system state space equation; two-wheeled self-balancing robot; Adaptation models; Analytical models; DC motors; Mathematical model; Training; Wheels; adaptive neural network fuzzy control; robot modeling; two-wheeled self-balancing robot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Strategic Technology (IFOST), 2011 6th International Forum on
Conference_Location :
Harbin, Heilongjiang
Print_ISBN :
978-1-4577-0398-0
Type :
conf
DOI :
10.1109/IFOST.2011.6021194
Filename :
6021194
Link To Document :
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