Fuzzy logic control with genetic membership function parameters optimization for the output regulation of a servomechanism with nonlinear backlash

The paper presents a hybrid architecture, which combines Type-1 or Type-2 fuzzy logic system (FLS) and genetic algorithms (GAs) for the optimization of the membership function (MF) parameters of FLS, in order to solve to the output regulation problem of a servomechanism with nonlinear backlash. In t...

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Veröffentlicht in:Expert systems with applications 2010-06, Vol.37 (6), p.4368-4378
Hauptverfasser: Cazarez-Castro, Nohe R., Aguilar, Luis T., Castillo, Oscar
Format: Artikel
Sprache:eng
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Zusammenfassung:The paper presents a hybrid architecture, which combines Type-1 or Type-2 fuzzy logic system (FLS) and genetic algorithms (GAs) for the optimization of the membership function (MF) parameters of FLS, in order to solve to the output regulation problem of a servomechanism with nonlinear backlash. In this approach, the fuzzy rule base is predesigned by experts of this problem. The proposed method is far from trivial because of nonminimum phase properties of the system. The simulation results illustrate the effectiveness of the optimized closed-loop system.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2009.11.091