Fuzzy identification of unknown systems based on GA

1997 ◽  
pp. 216-223 ◽  
Author(s):  
Jee-Hyong Lee ◽  
Hyung Lee-Kwang
Keyword(s):  
Fuzzy Identification

Design of back propagation optimized Nagar-Bardini structure-based interval type-2 fuzzy logic systems for fuzzy identification

2021 ◽  
pp. 014233122110066
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Back Propagation ◽  
Membership Functions ◽  
Identification Problems ◽  
Fuzzy Logic Systems ◽  
Fuzzy Identification ◽  
Logic Systems ◽  
Academic Topic ◽  
Interval Type

In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.

Fuzzy identification of a greenhouse

2007 ◽  
Vol 7 (3) ◽  
pp. 1092-1101 ◽  
Author(s):  
Amine Trabelsi ◽  
Frederic Lafont ◽  
Mohamed Kamoun ◽  
Gilles Enea
Keyword(s):  
Fuzzy Identification

scholarly journals Residual Generator Fuzzy Identification for Wind TurbineBenchmark Fault Diagnosis

Machines ◽  
2014 ◽  
Vol 2 (4) ◽  
pp. 275-298 ◽  
Author(s):  
Silvio Simani ◽  
Saverio Farsoni ◽  
Paolo Castaldi
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Identification ◽  
Residual Generator

Fuzzy identification of dynamic loads in presence of structural epistemic uncertainties

2020 ◽  
Vol 360 ◽  
pp. 112718
Author(s):  
Menghui Xu ◽  
Jiahan Huang ◽  
Chong Wang ◽  
Yunlong Li
Keyword(s):  
Dynamic Loads ◽  
Fuzzy Identification

scholarly journals Single Pole-to-Ground Fault Analysis of MMC-HVDC Transmission Lines Based on Capacitive Fuzzy Identification Algorithm

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 319
Author(s):  
Hongchun Shu ◽  
Na An ◽  
Bo Yang ◽  
Yue Dai ◽  
Yu Guo
Keyword(s):  
Transmission Lines ◽  
Fault Analysis ◽  
Identification Algorithm ◽  
Discharge Process ◽  
Multilevel Converter ◽  
Fuzzy Identification ◽  
Hvdc Transmission ◽  
High Voltage Direct Current ◽  
Ground Fault ◽  
Hvdc Transmission Lines

The probability of a single pole-to-ground fault in high voltage direct current (HVDC) transmission lines is relatively high. For the modular multilevel converter HVDC (MMC-HVDC) systems, when a single pole-to-ground fault occurs, the fault current is small, and it is difficult to identify the fault quickly. Through a detailed analysis of the characteristics of the single pole-to-ground fault of the MMC-HVDC transmission line, it is found that the single pole-to-ground fault has obvious capacitance-related characteristics, and the transient process after the single pole-to-ground fault is the discharge process of the distributed capacitance of the line. However, other faults do not have such obvious capacitance-related characteristics. Based on such feature, this paper proposes a novel capacitive fuzzy identification method to identify the single pole-to-ground fault. This algorithm can effectively identify both the fault of single pole-to-ground and the fault pole, which can contribute to the large database of the future smart grid.

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