Cuckoo search-based T-S fuzzy identification of nonlinear systems

Author

Turki, Mourad ; Sakly, Anis

Author_Institution

Res. Unit Etude des Syst. Ind. et Energies Renouvelables), Nat. Sch. of Eng. of Monastir, Monastir, Tunisia

fYear

2015

fDate

28-30 April 2015

Firstpage

151

Lastpage

154

Abstract

This paper proposes a novel metaheuristic optimization algorithm called Cuckoo Search CS to extract T-S model. In this study, the structure and parameters of the fuzzy model are encoded into a particle. Thus, the optimal structure and parameters are achieved simultaneously. The proposed method was compared with the particle swarm optimization PSO through a modelling problem. The results prove that CS method represents a powerful search approach and an effective optimization technique especially in the mean and standard deviation of MSE.

Keywords

fuzzy set theory; identification; nonlinear control systems; search problems; CS method; MSE; PSO; T-S model; cuckoo search-based T-S fuzzy identification; fuzzy model parameters; fuzzy model structure; mean deviation; metaheuristic optimization algorithm; modelling problem; nonlinear systems; optimal structure; optimization technique; particle swarm optimization; search approach; standard deviation; Cybernetics; Mathematical model; Optimization; Sociology; Standards; Statistics; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Control (ICSC), 2015 4th International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-7108-7

Type

conf

DOI

10.1109/ICoSC.2015.7153292

Filename

7153292