Fuzzy Network-Based Control for a Class of T–S Fuzzy Systems with Limited Communication

Author(s):  
M. Kchaou ◽  
A. Toumi
2020 ◽  
pp. 002029402097022
Author(s):  
Yinlin Li ◽  
Lihao Jia ◽  
Yidao Ji ◽  
Rui Li

Modern network applications place higher demands on its controller, especially for those with time-varying delays and limited communication capacity. For such cases, the fuzzy system has already become an advanced and powerful tool to deal with the control problem in consideration of a guaranteed cost performance. In this paper, we introduce the event-triggered mechanism with quantization effect to the controller, which proves to be more effective in terms of the information transmission. We adopt the classical Lyapunov approach to find the sufficient conditions for the controller and we illustrate the effectiveness of the controller with a numerical simulation.


Author(s):  
Abdul Malek Yaakob ◽  
Shahira Shafie ◽  
Alexander Gegov ◽  
Siti Fatimah Abdul Rahman

AbstractDecision-making environment often encounters complexity along its processes, especially in the context of multidisciplinary scientific research. This can commonly be seen in engineering, computing, finance, astrology and other different areas. It is of great restriction in dealing with the practical problems which have diverse demands and properties. There is a growing body of literature that recognizes the importance of dealing with the complexity in decision making environment. The reliability and the transparency are the dominant feature of the integration of fuzzy network and Z-numbers. However, much of the research up to now has been descriptive in nature of the features. Hence, this proposed method is unique and novel because it offers some interesting insight of dealing with reliability and transparency of information in Z-hesitant fuzzy network decision-making environment. The fuzzy networks have the functionality under rule bases of fuzzy systems where it is recognized by its transparency and precision. The proposed method makes use of fuzzy network with the incorporation of hesitant fuzzy sets to assimilate decision information towards alternatives. For the validation and applicability purposes of the proposed method, the case study of stock evaluation assessed by a number of decision makers has been utilized as a real-world problem. The performance of the proposed method is evaluated respectively by applying the Spearman’s rho correlation. The result shows that the proposed method performs as the established method with the consideration of additional dominant features.


2021 ◽  
pp. 1-18
Author(s):  
Tanveen Kaur Bhatia ◽  
Amit Kumar ◽  
S.S. Appadoo

Enayattabr et al. (Journal of Intelligent and Fuzzy Systems 37 (2019) 6865– 6877) claimed that till now no one has proposed an approach to solve interval-valued trapezoidal fuzzy all-pairs shortest path problems (all-pairs shortest path problems in which distance between every two nodes is represented by an interval-valued trapezoidal fuzzy number). Also, to fill this gap, Enayattabr et al. proposed an approach to solve interval-valued trapezoidal fuzzy all-pairs shortest path problems. In this paper, an interval-valued trapezoidal fuzzy shortest path problem is considered to point out that Enayattabr et al.’s approach fails to find correct shortest distance between two fixed nodes. Hence, it is inappropriate to use Enayattabr et al.’s approach in its present from. Also, the required modifications are suggested to resolve this inappropriateness of Enayattabr et al.’s approach.


2001 ◽  
Vol 32 (7) ◽  
pp. 915-924 ◽  
Author(s):  
Jun Yoneyama ◽  
Masahiro Nishikawa ◽  
Hitoshi Katayama ◽  
Akira Ichikawa
Keyword(s):  

2011 ◽  
Vol 7 (2) ◽  
pp. 102-106 ◽  
Author(s):  
Taqwa Odey Fahad ◽  
Abduladhim A. Ali
Keyword(s):  

2013 ◽  
Vol 58 (3) ◽  
pp. 871-875
Author(s):  
A. Herberg

Abstract This article outlines a methodology of modeling self-induced vibrations that occur in the course of machining of metal objects, i.e. when shaping casting patterns on CNC machining centers. The modeling process presented here is based on an algorithm that makes use of local model fuzzy-neural networks. The algorithm falls back on the advantages of fuzzy systems with Takagi-Sugeno-Kanga (TSK) consequences and neural networks with auxiliary modules that help optimize and shorten the time needed to identify the best possible network structure. The modeling of self-induced vibrations allows analyzing how the vibrations come into being. This in turn makes it possible to develop effective ways of eliminating these vibrations and, ultimately, designing a practical control system that would dispose of the vibrations altogether.


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