DocumentCode
2520756
Title
Research on fuzzy neural network-based sliding mode balance control of Acrobot
Author
Bo, Liu ; Yan, Zheng
Author_Institution
Northeastern Univ., Shenyang, China
fYear
2011
fDate
23-25 May 2011
Firstpage
3416
Lastpage
3421
Abstract
Acrobot is a kind of under-actuated two-link rods robot. The control methods of Acrobot are complicated, but doing research on it is valuable to the applications and the study of nonlinear systems. Balance control and swing-up control are two main control areas of Acrobot. This paper centers on its balance control and combines the advantages of sliding mode control and fuzzy neural network to control Acrobot system. The simulations show that the new control strategy proposed in this paper is more effective than SMC (Sliding Mode Control) or ANFIS (Adaptive-Neural Network-based Fuzzy Inference System) respectively used to control Acrobot.
Keywords
fuzzy control; mobile robots; neurocontrollers; nonlinear control systems; variable structure systems; Acrobot system; fuzzy neural network; nonlinear system; sliding mode balance control; swing-up control; two-link rods robot; Artificial neural networks; Fuzzy control; Mathematical model; Simulation; Sliding mode control; Solid modeling; ANFIS; Acrobot; LQR; Sliding Mode Control;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location
Mianyang
Print_ISBN
978-1-4244-8737-0
Type
conf
DOI
10.1109/CCDC.2011.5968706
Filename
5968706
Link To Document