Fast incremental best estimate directed search-a significantly expedited algorithm for Takagi-Sugeno type fuzzy logic controller automatic optimization

2005 ◽  
Author(s):  
Feijun Song ◽  
S.M. Smith
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Directed Search ◽  
Best Estimate ◽  
Automatic Optimization ◽  
Takagi Sugeno

scholarly journals Self-tuning Fuzzy Logic Controller Based on Takagi-Sugeno Applied to Induction Motor Drives

2018 ◽  
Vol 9 (4) ◽  
pp. 1967 ◽  
Author(s):  
Nabil Farah ◽  
M. H. N. Talib ◽  
Z. Ibrahim ◽  
J. M. Lazi ◽  
Maaspaliza Azri
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Experimental Testing ◽  
Motor Drives ◽  
Computational Burden ◽  
Response Characteristics ◽  
Speed Error ◽  
Self Tuning ◽  
Takagi Sugeno

<span>Fuzzy logic controller has been the main focus for many researchers and industries in motor drives. The popularity of Fuzzy Logic Controller (FLC) is due to its reliability and ability to handle parameters changes during load or disturbance. Fuzzy logic design can be visualized in two categories, mamdani design or Takagi-Sugeno (TS). Mamdani type can facilitate the design process, however it require high computational burden especially with big number of rules and experimental testing. This paper, develop Self-Tuning (ST) mechanism based on Takagi-Sugeno (TS) fuzzy type. The mechanism tunes the input scaling factor of speed fuzzy control of Induction Motor (IM) drives Based on the speed error and changes of error. A comparison study is done between the standard TS and the ST-TS based on simulations approaches considering different speed operations. Speed response characteristics such as rise time, overshoot, and settling time are compared for ST-TS and TS. It was shown that ST-TS has optimum results compared to the standard TS. The significance of the proposed method is that, optimum computational burden reduction is achieved.</span>

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