Intuitionistic Neo-Fuzzy predictive control

Margarita Terziyska, Yancho Todorov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)

Abstract

This paper presents an implicit predictive control strategy based on Intuitionistic Neo-Fuzzy predictor, as a first attempt to investigate the potentials of the intuitionistic fuzzy logic for the purpose of control applications. The proposed predictor represents a simple fuzzy-neural network as fusion from the concepts of the intuitionistic fuzzy logic, the neo-fuzzy neuron theory and the classical Takagi-Sugeno inference mechanism. The predictions are then coupled into generalized predictive control scheme where a standard quadratic control cost function is minimized over a set of predefined horizons. For simplicity, the considered process variables and the calculated output control sequence are iteratively bounded instead of explicitly constrained, in order to investigate the computational procedures related to implementation of an intuitionistic fuzzy logic. To investigate the potentials of the proposed predictive control approach, numerical experiments to control a Continuous Stirred Tank Reactor (CSTR) under uncertain conditions are studied.

Original languageEnglish
Title of host publication2016 IEEE 8th International Conference on Intelligent Systems, IS 2016
EditorsVassil Sgurev, Ronald Yager, Mincho Hadjiski, Vladimir Jotsov
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages635-640
ISBN (Electronic)978-1-5090-1354-8, 978-1-5090-1353-1
ISBN (Print)978-1-5090-1355-5
DOIs
Publication statusPublished - 7 Nov 2016
MoE publication typeA4 Article in a conference publication
Event8th IEEE International Conference on Intelligent Systems, IS 2016 - Sofia, Bulgaria
Duration: 4 Sep 20166 Sep 2016

Conference

Conference8th IEEE International Conference on Intelligent Systems, IS 2016
CountryBulgaria
CitySofia
Period4/09/166/09/16

Fingerprint

Intuitionistic Logic
Predictive Control
Fuzzy Control
Fuzzy Logic
Predictors
Generalized Predictive Control
Fuzzy logic
Fuzzy Neural Network
Control Function
Reactor
Cost Function
Control Strategy
Horizon
Neuron
Simplicity
Fusion
Numerical Experiment
Prediction
Output
Fuzzy neural networks

Keywords

  • Continuous Stirred Tank Reactor
  • Intuitionistic Fuzzy Logic
  • Intuitionistic Neo-Fuzzy Network
  • Model Predictive Control
  • Neo-Fuzzy Network

Cite this

Terziyska, M., & Todorov, Y. (2016). Intuitionistic Neo-Fuzzy predictive control. In V. Sgurev, R. Yager, M. Hadjiski, & V. Jotsov (Eds.), 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 (pp. 635-640). [7737494] Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/IS.2016.7737494
Terziyska, Margarita ; Todorov, Yancho. / Intuitionistic Neo-Fuzzy predictive control. 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016. editor / Vassil Sgurev ; Ronald Yager ; Mincho Hadjiski ; Vladimir Jotsov. Institute of Electrical and Electronic Engineers IEEE, 2016. pp. 635-640
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Terziyska, M & Todorov, Y 2016, Intuitionistic Neo-Fuzzy predictive control. in V Sgurev, R Yager, M Hadjiski & V Jotsov (eds), 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016., 7737494, Institute of Electrical and Electronic Engineers IEEE, pp. 635-640, 8th IEEE International Conference on Intelligent Systems, IS 2016, Sofia, Bulgaria, 4/09/16. https://doi.org/10.1109/IS.2016.7737494

Intuitionistic Neo-Fuzzy predictive control. / Terziyska, Margarita; Todorov, Yancho.

2016 IEEE 8th International Conference on Intelligent Systems, IS 2016. ed. / Vassil Sgurev; Ronald Yager; Mincho Hadjiski; Vladimir Jotsov. Institute of Electrical and Electronic Engineers IEEE, 2016. p. 635-640 7737494.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Terziyska M, Todorov Y. Intuitionistic Neo-Fuzzy predictive control. In Sgurev V, Yager R, Hadjiski M, Jotsov V, editors, 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016. Institute of Electrical and Electronic Engineers IEEE. 2016. p. 635-640. 7737494 https://doi.org/10.1109/IS.2016.7737494