Performance enhancement of fuzzy logic controller using robust fixed point transformation

Adrienn Dineva, A. Várkonyi-Kóczy, J. Tar, Vincenzo Piuri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Despite its excellent performance as a controller for linear and non-linear systems, the fuzzy logic controller has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems are used in various applications with large number of rules. Furthermore, the results also depend on the selected membership functions, etc. This paper presents a novel framework that instead of reducing the number of rules for a fuzzy logic controller, combines it with a fixed point transformation based adaptive control. The adopted approach is based on the Mamdani-type fuzzy controller and enhanced by the Sigmoid Generated Fixed Point Transformation control strategy to cope with modeling inaccuracies and external disturbances that can arise. The general procedure is applied to a nonlinear Kapitza pendulum. Numerical simulations are validating the applicability of the proposed scheme and demonstrating the controller’s performance.

Original languageEnglish
Title of host publicationRecent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016
PublisherSpringer Verlag
Pages411-418
Number of pages8
Volume519
ISBN (Print)9783319464893
DOIs
Publication statusPublished - 2017
Event15th International Conference on Global Research and Education, INTER-ACADEMIA 2016 - Warsaw, Poland
Duration: Sep 26 2016Sep 28 2016

Publication series

NameAdvances in Intelligent Systems and Computing
Volume519
ISSN (Print)21945357

Other

Other15th International Conference on Global Research and Education, INTER-ACADEMIA 2016
CountryPoland
CityWarsaw
Period9/26/169/28/16

Fingerprint

Fuzzy logic
Controllers
Fuzzy systems
Membership functions
Pendulums
Nonlinear systems
Computer simulation

Keywords

  • Adaptive control
  • Fuzzy logic
  • Iterative learning control
  • Sigmoid generated fixed point transformation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Dineva, A., Várkonyi-Kóczy, A., Tar, J., & Piuri, V. (2017). Performance enhancement of fuzzy logic controller using robust fixed point transformation. In Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016 (Vol. 519, pp. 411-418). (Advances in Intelligent Systems and Computing; Vol. 519). Springer Verlag. https://doi.org/10.1007/978-3-319-46490-9_55

Performance enhancement of fuzzy logic controller using robust fixed point transformation. / Dineva, Adrienn; Várkonyi-Kóczy, A.; Tar, J.; Piuri, Vincenzo.

Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519 Springer Verlag, 2017. p. 411-418 (Advances in Intelligent Systems and Computing; Vol. 519).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dineva, A, Várkonyi-Kóczy, A, Tar, J & Piuri, V 2017, Performance enhancement of fuzzy logic controller using robust fixed point transformation. in Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. vol. 519, Advances in Intelligent Systems and Computing, vol. 519, Springer Verlag, pp. 411-418, 15th International Conference on Global Research and Education, INTER-ACADEMIA 2016, Warsaw, Poland, 9/26/16. https://doi.org/10.1007/978-3-319-46490-9_55
Dineva A, Várkonyi-Kóczy A, Tar J, Piuri V. Performance enhancement of fuzzy logic controller using robust fixed point transformation. In Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519. Springer Verlag. 2017. p. 411-418. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-46490-9_55
Dineva, Adrienn ; Várkonyi-Kóczy, A. ; Tar, J. ; Piuri, Vincenzo. / Performance enhancement of fuzzy logic controller using robust fixed point transformation. Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016. Vol. 519 Springer Verlag, 2017. pp. 411-418 (Advances in Intelligent Systems and Computing).
@inproceedings{8d9ab11487b24ce6953b5e1bd28c7253,
title = "Performance enhancement of fuzzy logic controller using robust fixed point transformation",
abstract = "Despite its excellent performance as a controller for linear and non-linear systems, the fuzzy logic controller has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems are used in various applications with large number of rules. Furthermore, the results also depend on the selected membership functions, etc. This paper presents a novel framework that instead of reducing the number of rules for a fuzzy logic controller, combines it with a fixed point transformation based adaptive control. The adopted approach is based on the Mamdani-type fuzzy controller and enhanced by the Sigmoid Generated Fixed Point Transformation control strategy to cope with modeling inaccuracies and external disturbances that can arise. The general procedure is applied to a nonlinear Kapitza pendulum. Numerical simulations are validating the applicability of the proposed scheme and demonstrating the controller’s performance.",
keywords = "Adaptive control, Fuzzy logic, Iterative learning control, Sigmoid generated fixed point transformation",
author = "Adrienn Dineva and A. V{\'a}rkonyi-K{\'o}czy and J. Tar and Vincenzo Piuri",
year = "2017",
doi = "10.1007/978-3-319-46490-9_55",
language = "English",
isbn = "9783319464893",
volume = "519",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "411--418",
booktitle = "Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016",

}

TY - GEN

T1 - Performance enhancement of fuzzy logic controller using robust fixed point transformation

AU - Dineva, Adrienn

AU - Várkonyi-Kóczy, A.

AU - Tar, J.

AU - Piuri, Vincenzo

PY - 2017

Y1 - 2017

N2 - Despite its excellent performance as a controller for linear and non-linear systems, the fuzzy logic controller has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems are used in various applications with large number of rules. Furthermore, the results also depend on the selected membership functions, etc. This paper presents a novel framework that instead of reducing the number of rules for a fuzzy logic controller, combines it with a fixed point transformation based adaptive control. The adopted approach is based on the Mamdani-type fuzzy controller and enhanced by the Sigmoid Generated Fixed Point Transformation control strategy to cope with modeling inaccuracies and external disturbances that can arise. The general procedure is applied to a nonlinear Kapitza pendulum. Numerical simulations are validating the applicability of the proposed scheme and demonstrating the controller’s performance.

AB - Despite its excellent performance as a controller for linear and non-linear systems, the fuzzy logic controller has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems are used in various applications with large number of rules. Furthermore, the results also depend on the selected membership functions, etc. This paper presents a novel framework that instead of reducing the number of rules for a fuzzy logic controller, combines it with a fixed point transformation based adaptive control. The adopted approach is based on the Mamdani-type fuzzy controller and enhanced by the Sigmoid Generated Fixed Point Transformation control strategy to cope with modeling inaccuracies and external disturbances that can arise. The general procedure is applied to a nonlinear Kapitza pendulum. Numerical simulations are validating the applicability of the proposed scheme and demonstrating the controller’s performance.

KW - Adaptive control

KW - Fuzzy logic

KW - Iterative learning control

KW - Sigmoid generated fixed point transformation

UR - http://www.scopus.com/inward/record.url?scp=84989933530&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84989933530&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-46490-9_55

DO - 10.1007/978-3-319-46490-9_55

M3 - Conference contribution

SN - 9783319464893

VL - 519

T3 - Advances in Intelligent Systems and Computing

SP - 411

EP - 418

BT - Recent Global Research and Education: Technological Challenges - Proceedings of the 15th International Conference on Global Research and Education Inter-Academia 2016

PB - Springer Verlag

ER -