Beam and Ball Plant System Controlling Using Intuitionistic Fuzzy Control

2021 ◽  
pp. 255-262
Author(s):  
Onur Silahtar ◽  
Özkan Atan ◽  
Fatih Kutlu ◽  
Oscar Castillo
Keyword(s):  
Fuzzy Control ◽  
Plant System ◽  
Intuitionistic Fuzzy

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

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.

Intuitionistic fuzzy c-control charts using defuzzification and likelihood methods

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.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

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