Structure identification of fuzzy model
Fuzzy Sets and Systems
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Swarm intelligence
Particle Swarm Optimization (PSO) applied to Fuzzy Modeling in a Thermal-Vacuum System
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
IEEE Transactions on Evolutionary Computation
Fuzzy logic models for ranking process effects
IEEE Transactions on Fuzzy Systems
Fuzzy piecewise multilinear and piecewise linear systems as universal approximators in Sobolev norms
IEEE Transactions on Fuzzy Systems
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Particle Swarm Optimization with Turbulence (PSOT) is, in this paper, applied to find out fuzzy models to represent dynamic behavior of space systems that lie underneath the space qualification process. In optimization area, each minimal improvement in results may represents a maximal, precious meaning and PSOT improve the performance of the established Particle Swarm Optimization (PSO) by introducing a slight variation, which simulates the action of an atmosphere turbulence to escape from local minima. This paper trades off the results of original PSO presented in a previous paper nd PSOT both intertwined with Takagi-Sugeno (TS) fuzzy modeling dealing with experimental results of a thermal-vacuum system. Particle Swarm Optimization with turbulence has demonstrated to be a good alternative by taking into account the velocity of convergence to better solution and the total optimization time in generating dynamical models to the proposed system.