Title :
Intelligent Neural Sliding Control for Planetary Gear Type Inverted Pendulum Mechanism
Author :
Huang, Y.J. ; Hsu, C.Y. ; Kuo, T.C. ; Lin, J.
Author_Institution :
Yuan Ze Univ., Jung-Li
Abstract :
An intelligent neural sliding controller is developed for planetary train type inverted pendulum mechanism. The control methodology is based on the sliding mode control. The switching function in the normal control law is replaced with a bipolar sigmoid function. A fuzzy neural network is used to identify the pendulum dynamics. Adaptive tuning law is derived. The bipolar sigmoid function is thus adjusted according to the result of the identification process.
Keywords :
adaptive control; control system synthesis; fuzzy control; fuzzy neural nets; gears; neurocontrollers; nonlinear control systems; pendulums; variable structure systems; adaptive tuning law; bipolar sigmoid function; fuzzy neural network; intelligent neural sliding mode control; planetary train type gear inverted pendulum; Control systems; Friction; Fuzzy control; Fuzzy neural networks; Gears; Intelligent control; Planets; Robust control; Servomotors; Sliding mode control;
Conference_Titel :
Intelligent Control, 2007. ISIC 2007. IEEE 22nd International Symposium on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-0440-7
Electronic_ISBN :
2158-9860
DOI :
10.1109/ISIC.2007.4450935