Intuitionistic Fuzzy Control Based on Association Rules

In the field of fuzzy control, the generation of fuzzy control rules has always been a problem, because the industrial data is generally expressed in the order of time ,so it strongly depends on the time, it does not take the factors of temporal constraints into account in the previous extracting rule process.This paper uses temporal constraint association rule ,and uses the data mining methods to generate temporal fuzzy control rules. The method is verified by using the MATLAB7.1 ,the simulation shows that the method can achieve good fuzzy control rules.

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Control and synchronization for two Chua systems based on intuitionistic fuzzy control scheme: A comparative study

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220981425 ◽

2021 ◽

pp. 014233122098142

Author(s):

Mohamed Hamdy ◽

Mohamed Magdy ◽

Salah Helmy

Keyword(s):

Fuzzy Control ◽

Comparative Study ◽

Chaotic Systems ◽

Initial Conditions ◽

External Disturbances ◽

Intuitionistic Fuzzy ◽

Control Scheme ◽

Simulation Results ◽

The Stability ◽

Control And Synchronization

This paper presents control and synchronization for two nonlinear chaotic systems in the presence of uncertainties and external disturbances based on an intuitionistic fuzzy control (IFC) scheme. Two classes of Chua and cubic Chua oscillators have been formulated as master and slave respectively. The master and slave systems have different initial conditions and parameters, which leads to the butterfly effect that rules the chaotic systems’ behaviour. IFC scheme is chosen as a different method that has not been used before to control and synchronize Chua and cubic Chua oscillators. The main objective of the IFC scheme is to collect more information about the system and provide flexibility for the controller that increases the robustness of the control system to uncertainties in the structure of the chaotic systems. The stability analysis of the overall system is guaranteed using Routh-Hurwitz and Lyapunov criteria. The simulation results accomplished to evaluate the effectiveness of the proposed control and to demonstrate its reliability to control Chua’s circuit system with a comparative study.

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Intuitionistic fuzzy c-control charts using defuzzification and likelihood methods

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189110 ◽

2020 ◽

Vol 39 (5) ◽

pp. 6465-6473

Author(s):

Hatice Ercan-Teksen ◽

Ahmet Sermet Anagün

Keyword(s):

Fuzzy Control ◽

Fuzzy Sets ◽

Control Chart ◽

Control Charts ◽

Intuitionistic Fuzzy Sets ◽

Likelihood Method ◽

Likelihood Methods ◽

Qualitative And Quantitative ◽

Intuitionistic Fuzzy

Control chart is one of the statistical methods to analyze the process. The use of fuzzy sets in control charts, which are divided into qualitative and quantitative data, has been applied in many studies recently. Especially for qualitative control charts, data collection is more difficult and more subjective. Therefore, fuzzy sets are used to reduce losses in data. There are many control chart studies created by type-1 fuzzy sets available in the literature. In recent years, examples of fuzzy control charts with extensions of fuzzy sets have been found. The aim of this study is to obtain c-control chart for intuitionistic fuzzy sets. For this purpose, defuzzification and likelihood methods are used. In particular, with the application of the likelihood method to intuitionistic fuzzy control charts, this will be considered as a pioneering study in the literature. In addition, a novel likelihood method was developed for intuitionistic fuzzy sets and used here to provide flexibility.

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