Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs

Cristian Guarnizo Lemus, Alejandro Restrepo Martinez

2012

Abstract

An approach to fuzzy identification of discrete time nonlinear dynamical systems based on the Takagi-Sugeno (TS) model with a economical computation formulation is proposed. Number of rules and membership functions positions are fixed for all inputs. This allows to avoid the fuzzification proccess of delayed inputs. Rule base evaluation is avoided for delayed inputs by the Reusable Fuzzified Inputs approach. Consequent parameters are trained or estaimated using least squares approach. This method is intended to be trained in an off-line manner and used in programmable devices. Finally, simulations are performed on two diffrerent problems, the approach shows consistency, tracking of the output that vary with time and a high accuracy of the output estimate, properties requiered in control design applications.

References

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Paper Citation


in Harvard Style

Guarnizo Lemus C. and Restrepo Martinez A. (2012). Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 424-428. DOI: 10.5220/0004157904240428


in Bibtex Style

@conference{fcta12,
author={Cristian Guarnizo Lemus and Alejandro Restrepo Martinez},
title={Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2012)},
year={2012},
pages={424-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004157904240428},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2012)
TI - Non-linear System Identification by a Fuzzy Takagi-Sugeno System Approach based on Reusable Fuzzified Inputs
SN - 978-989-8565-33-4
AU - Guarnizo Lemus C.
AU - Restrepo Martinez A.
PY - 2012
SP - 424
EP - 428
DO - 10.5220/0004157904240428