Optimal Control Using Feedback Linearization for a Generalized T-S Model
Data(s) |
2014
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Resumo |
In this paper, a fuzzy feedback linearization is used to control nonlinear systems described by Takagi-Suengo (T-S) fuzzy systems. In this work, an optimal controller is designed using the linear quadratic regulator (LQR). The well known weighting parameters approach is applied to optimize local and global approximation and modelling capability of T-S fuzzy model to improve the choice of the performance index and minimize it. The approach used here can be considered as a generalized version of T-S method. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the proposed optimal LQR algorithm. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
E.T.S.I. Industriales (UPM) |
Relação |
http://oa.upm.es/38720/1/INVE_MEM_2014_212698.pdf http://link.springer.com/chapter/10.1007%2F978-3-662-44654-6_46 PI2010-21247-C02-01 info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-662-44654-6 |
Direitos |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/restrictedAccess |
Fonte |
Optimal Control Using Feedback Linearization for a Generalized T-S Model | En: Artificial Intelligence Applications and Innovations. 10th IFIP WG 12.5 International Conference, AIAI 2014, Rhodes, Greece, September 19-21, 2014. Proceedings | pag. 466-475 | Springer | 2014 |
Palavras-Chave | #Robótica e Informática Industrial |
Tipo |
info:eu-repo/semantics/bookPart Sección de Libro PeerReviewed |