A new approach to fuzzy estimation of Takagi-Sugeno model and its applications to optimal control for nonlinear systems

Al-Hadithi, Basil M.; Jiménez Avello, Agustín y Matía Espada, Fernando (2012). A new approach to fuzzy estimation of Takagi-Sugeno model and its applications to optimal control for nonlinear systems. "Applied Soft Computing", v. 12 (n. 1); pp. 280-290. ISSN 1568-4946. https://doi.org/10.1016/j.asoc.2011.08.044.

Descripción

Título: A new approach to fuzzy estimation of Takagi-Sugeno model and its applications to optimal control for nonlinear systems
Autor/es:
  • Al-Hadithi, Basil M.
  • Jiménez Avello, Agustín
  • Matía Espada, Fernando
Tipo de Documento: Artículo
Título de Revista/Publicación: Applied Soft Computing
Fecha: Enero 2012
Volumen: 12
Materias:
Palabras Clave Informales: Nonlinear systems, Dynamics, Fuzzy systems, Modeling, Fuzzy control
Escuela: E.U.I.T. Industrial (UPM) [antigua denominación]
Departamento: Electrónica, Automática e Informática Industrial [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

An efficient approach is presented to improve the local and global approximation and modelling capability of Takagi-Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy. The main problem is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the use of the T-S method because this type of membership function has been widely used during the last two decades in the stability, controller design and are popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S method with optimized performance in approximating nonlinear functions. A simple approach with few computational effort, based on the well known parameters' weighting method is suggested for tuning T-S parameters to improve the choice of the performance index and minimize it. A global fuzzy controller (FC) based Linear Quadratic Regulator (LQR) is proposed in order to show the effectiveness of the estimation method developed here in control applications. Illustrative examples of an inverted pendulum and Van der Pol system are chosen to evaluate the robustness and remarkable performance of the proposed method and the high accuracy obtained in approximating nonlinear and unstable systems locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the algorithm.

Más información

ID de Registro: 16302
Identificador DC: http://oa.upm.es/16302/
Identificador OAI: oai:oa.upm.es:16302
Identificador DOI: 10.1016/j.asoc.2011.08.044
URL Oficial: http://www.sciencedirect.com/science/article/pii/S1568494611003279
Depositado por: Memoria Investigacion
Depositado el: 10 Oct 2013 11:57
Ultima Modificación: 01 Mar 2016 14:06
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