Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure

Reda Boukezzoula; Sylvie Galichet; Laurent Foulloy

International Journal of Applied Mathematics and Computer Science (2007)

  • Volume: 17, Issue: 2, page 233-248
  • ISSN: 1641-876X

Abstract

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This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model Control (NIMC) are investigated. Moreover, the paper points out that, under some conditions, both of the control structures are equivalent and naturally implement a Smith predictor in the presence of time delays.

How to cite

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Boukezzoula, Reda, Galichet, Sylvie, and Foulloy, Laurent. "Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure." International Journal of Applied Mathematics and Computer Science 17.2 (2007): 233-248. <http://eudml.org/doc/207834>.

@article{Boukezzoula2007,
abstract = {This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model Control (NIMC) are investigated. Moreover, the paper points out that, under some conditions, both of the control structures are equivalent and naturally implement a Smith predictor in the presence of time delays.},
author = {Boukezzoula, Reda, Galichet, Sylvie, Foulloy, Laurent},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {fuzzy control; internal model control; inverse control; feedback linearization},
language = {eng},
number = {2},
pages = {233-248},
title = {Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure},
url = {http://eudml.org/doc/207834},
volume = {17},
year = {2007},
}

TY - JOUR
AU - Boukezzoula, Reda
AU - Galichet, Sylvie
AU - Foulloy, Laurent
TI - Fuzzy feedback linearizing controller and its equivalence with the fuzzy nonlinear internal model control structure
JO - International Journal of Applied Mathematics and Computer Science
PY - 2007
VL - 17
IS - 2
SP - 233
EP - 248
AB - This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model Control (NIMC) are investigated. Moreover, the paper points out that, under some conditions, both of the control structures are equivalent and naturally implement a Smith predictor in the presence of time delays.
LA - eng
KW - fuzzy control; internal model control; inverse control; feedback linearization
UR - http://eudml.org/doc/207834
ER -

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Citations in EuDML Documents

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  1. Jimoh Olarewaju Pedro, Olurotimi Akintunde Dahunsi, Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system
  2. Dezhi Xu, Bin Jiang, Peng Shi, Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model
  3. Shaocheng Tong, Changliang Liu, Yongming Li, Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems
  4. Shaocheng Tong, Gengjiao Yang, Wei Zhang, Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays
  5. Łukasz Bartczuk, Andrzej Przybył, Krzysztof Cpałka, A new approach to nonlinear modelling of dynamic systems based on fuzzy rules

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