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Design and optimization of TS firefly algorithm based on the nonhomogeneous linear polygonal T‐S fuzzy system
Author(s) -
Wang Guijun,
Chen Xue,
Sun Gang
Publication year - 2021
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22316
Subject(s) - fuzzy logic , representation (politics) , algorithm , firefly algorithm , fuzzy number , mathematics , nonlinear system , computer science , expression (computer science) , fuzzy control system , mathematical optimization , fuzzy set , artificial intelligence , particle swarm optimization , physics , quantum mechanics , politics , political science , law , programming language
The core idea of the fuzzy system is to avoid the accurate mathematical model and imitate human brain to achieve fuzzy reasoning, it can not only convert language information into a systematic program of nonlinear mapping, but also process complex data information through fuzzy rules. In this paper, we first introduce the mathematical model of the nonhomogeneous linear polygonal Takagi–Sugeno (T‐S) fuzzy system based on the ordered representation of polygonal fuzzy number and its linear operation, and the expression of the adjustment parameters of the consequent linear part of the T‐S fuzzy system is given by the ordered representation. Second, the relative brightness and attraction formula of firefly are used to update the particle positions of possible solutions, thus achieving global optimization of all tuning parameters (particles). Finally, the TS firefly algorithm (TSFA) is designed for some adjustment parameters of the consequent part of the nonhomogeneous linear polygonal T‐S fuzzy system, and the effectiveness of the algorithm is illustrated by a simulation example.