Intuitionistic Neo-Fuzzy predictive control

Margarita Terziyska; Yancho Todorov

doi:10.1109/IS.2016.7737494

Intuitionistic Neo-Fuzzy predictive control

Margarita Terziyska, Yancho Todorov

Not published at VTT

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (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 language	English
Title of host publication	2016 IEEE 8th International Conference on Intelligent Systems, IS 2016
Editors	Vassil Sgurev, Ronald Yager, Mincho Hadjiski, Vladimir Jotsov
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	635-640
ISBN (Electronic)	978-1-5090-1354-8, 978-1-5090-1353-1
ISBN (Print)	978-1-5090-1355-5
DOIs	https://doi.org/10.1109/IS.2016.7737494
Publication status	Published - 7 Nov 2016
MoE publication type	A4 Article in a conference publication
Event	8th IEEE International Conference on Intelligent Systems, IS 2016 - Sofia, Bulgaria Duration: 4 Sept 2016 → 6 Sept 2016

Conference

Conference	8th IEEE International Conference on Intelligent Systems, IS 2016
Country/Territory	Bulgaria
City	Sofia
Period	4/09/16 → 6/09/16

Keywords

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

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10.1109/IS.2016.7737494

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title = "Intuitionistic Neo-Fuzzy predictive control",

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.",

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author = "Margarita Terziyska and Yancho Todorov",

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publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "8th IEEE International Conference on Intelligent Systems, IS 2016 ; Conference date: 04-09-2016 Through 06-09-2016",

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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, IEEE Institute of Electrical and Electronic Engineers, 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. IEEE Institute of Electrical and Electronic Engineers, 2016. p. 635-640 7737494.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Todorov, Yancho

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AB - 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.

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Intuitionistic Neo-Fuzzy predictive control

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