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Feb 26, 2008 · In this paper, a MagLev system is modeled by two self-organizing neural-fuzzy techniques to achieve linear and affine Takagi-Sugeno (T-S) fuzzy ...
Int. J. Robotics Autom. 2014. This research describes the controlled design and implementation of magnetic levitation application. The highly nonlinear ...
Mar 1, 2008 · 標題: Neural-fuzzy gap control for a current/voltage-controlled 1/4-vehicle MagLev system ; 作者: Wu, Shinq-Jen · Wu, Cheng-Tao · Chang, Yen-Chen
Neural-Fuzzy Gap Control for a Current/Voltage-Controlled 1/4-Vehicle MagLev System. IEEE Trans. Intell. Transp. Syst. 9(1): 122-136 (2008); 2003. [c1]. view.
In this paper, a MagLev system is modeled by two self-organizing neural-fuzzy techniques to achieve linear and affine Takagi-Sugeno (T-S) fuzzy systems. The ...
I. Papamichail and M. Papageorgiou. 111. Neural–Fuzzy Gap Control for a Current/Voltage-Controlled 1/4-Vehicle MagLev System .
This research work presents the modified cascade control scheme using the Fuzzy Tuner, implemented for the Electromagnetic Levitation System (EMLS), ...
Wu S.J., Wu C.T., Chang Y.C., 2008, Neural-fuzzy gap control for a current/voltage-controlled 1/4-vehicle MagLev system, IEEE Transactions on Intelligent ...
In this paper, a MagLev system is modeled by two self-organizing neural-fuzzy techniques to achieve linear and affine Takagi-Sugeno (T-S) fuzzy systems. The ...
This paper concerns with designing of a robust controller for Magnetic Levitation system exposed to external disturbances.