A nonlinear identification approach based on Particle Swarm Optimization (PSO) and Takagi-Sugeno (T-S) fuzzy model for describing dynamical behavior of a thermal-vacuum system is proposed in this paper. Identification of nonlinear systems is an important problem in engineering among what fuzzy models have received particular attention due to their potentialities to approximate nonlinear behavior. Meanwhile PSO is proposed as a method for optimizing the premise part of production rules, least mean squares technique is employed for consequent part of production rules of a T-S fuzzy model. Experimental application using a thermal-vacuum system, used for space environmental emulation and satellite qualification, is analyzed. Numerical results indicate that the PSO succeeded in constructing a T-S fuzzy model for nonlinear identification in this particular application.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Particle Swarm Optimization (PSO) applied to fuzzy modeling in a thermal-vacuum system


    Weitere Titelangaben:

    Teilchenschwarmoptimierung (PSO) für die Fuzzy-Modellbeschreibung in einem thermischen Vakuumsystem


    Beteiligte:


    Erscheinungsdatum :

    2005


    Format / Umfang :

    6 Seiten, 22 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch





    Adaptive Particle Swarm Optimization Applied to Aircraft Control

    Djaneye-Boundjou, Ouboti / Ordóñez, Raúl / Jacobsen, Lance | AIAA | 2015


    Particle swarm optimization applied to impulsive orbital transfers

    Pontani, Mauro / Conway, Bruce A. | Elsevier | 2011


    Particle Swarm Optimization Applied to Spacecraft Reentry Trajectory

    Rahimi, Afshin / Dev Kumar, Krishna / Alighanbari, Hekmat | AIAA | 2012