Design and optimization of TS firefly algorithm based on the nonhomogeneous linear polygonal T‐S fuzzy system
Guijun Wang, Xue Chen, Gang Sun · International Journal of Intelligent Systems · 2020
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.