The study of fuzzy-logic self-adaptive controller for UPFC

2008 ◽  
Author(s):  
Aihong Tang ◽  
Youxin Yuan ◽  
Shijie Cheng
Keyword(s):  
Fuzzy Logic ◽  
Adaptive Controller ◽  
Self Adaptive

scholarly journals Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

Decentralized fuzzy linguistic control of multiple robotic manipulators with guaranteed global stability

2019 ◽  
Vol 20 (1) ◽  
pp. 185-204
Author(s):  
Yongqing Fan ◽  
Wenqing Wang ◽  
Xiangkui Jiang ◽  
Zhen Li
Keyword(s):  
Fuzzy Logic ◽  
Global Stability ◽  
Fuzzy Controller ◽  
Robot Manipulators ◽  
Design Method ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Fuzzy Logic Systems ◽  
Approximation Accuracy ◽  
Logic Systems

Abstract A decentralized adaptive control based on human linguistic is investigated to learn human behaviors for multiple robotic manipulators. Many experts’ words or sentences can be transferred into the control actions by employing membership functions in robot systems, which can be synthesized fuzzy controller by employing reasoning mechanism. For the unknown model dynamical robot manipulators, one adjustable parameter that relates to the approximation accuracy of fuzzy logic systems is introduced at first, which be utilized to deal with the unknown dynamics of robot manipulators. Switching fuzzy adaptive controller is designed to overcome the limitation of logic structure that the number of adaptive laws only focus on fuzzy rules in conventional fuzzy logic systems. Another advantage of this design method is that the control with human linguistic extend the semi-global stability to global stability. Finally, effectiveness of the developed control design scheme has been shown in simulation example.

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