DocumentCode :
130132
Title :
Dynamic modeling and adaptive controller design for the track-stand motion of a front-wheel drive bicycle robot under 90 degrees front-bar steering angle
Author :
Deng Guo ; Lei Guo ; Shimin Wei ; Qizheng Liao
Author_Institution :
Sch. of Autom., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
966
Lastpage :
971
Abstract :
The track stand motion for the bicycle robot with front-wheel drive under 90 degrees front-bar turning angle is analyzed in this paper. A kind of dynamic model is proposed based on Appell Equation. To achieve the goal of track stand motion control, the controller is designed based on RBF neural network and adaptive sliding mode control algorithm. And the computer simulation is carried out based on MATLAB to compare the stable equilibrium motion of the robot without interference and under interference separately. The validity of the dynamic model and the control algorithm are testified by the simulation results. And the coefficients in the controller can be tuned automatically. The uncertainties in the model are estimated by the RBF neural network so that the controller is adaptive. Besides, it has certain ability of anti-interference.
Keywords :
adaptive control; control system synthesis; mobile robots; motion control; neurocontrollers; radial basis function networks; robot dynamics; variable structure systems; Appell equation; Matlab; RBF neural network; adaptive controller design; adaptive sliding mode control algorithm; dynamic modeling; front-bar steering angle; front-bar turning angle; front-wheel drive bicycle robot; radial basis function network; track stand motion control; Bicycles; Equations; Mathematical model; Neural networks; Robots; Turning; Wheels; Appell Equation; bicycle robot; dynamic model; neural network; sliding mode;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location :
Hailar
Type :
conf
DOI :
10.1109/ICInfA.2014.6932791
Filename :
6932791
Link To Document :
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