Relaxed Stability and Performance LMI Conditions for Takagi--Sugeno Fuzzy Systems With Polynomial Constraints on Membership Function Shapes

2008 ◽  
Vol 16 (5) ◽  
pp. 1328-1336 ◽  
Author(s):  
A. Sala ◽  
C. Arino
Keyword(s):  
Membership Function ◽  
Fuzzy Systems ◽  
And Performance ◽  
Takagi Sugeno ◽  
Polynomial Constraints

scholarly journals Less Conservative Fuzzy Control for Discrete-Time Takagi-Sugeno Systems

2011 ◽  
Vol 2011 ◽  
pp. 1-21 ◽  
Author(s):  
Leonardo Amaral Mozelli ◽  
Reinaldo Martinez Palhares
Keyword(s):  
Fuzzy Control ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Control Design ◽  
Practical Experiment ◽  
Numerical Tests ◽  
Slack Variables ◽  
And Performance ◽  
Takagi Sugeno ◽  
And Control

New analysis and control design conditions of discrete-time fuzzy systems are proposed. Using fuzzy Lyapunov's functions and introducing slack variables, less conservative conditions are obtained. The controller guarantees system stabilization and performance. Numerical tests and a practical experiment in Chua's circuit are presented to show the effectiveness.

H∞ control for Takagi–Sugeno fuzzy systems

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

Modeling of Self-Induced Vibrations that Occur During the Machining Process of Casting Patterns with the Use of The Fuzzy-Neural Networks Method

2013 ◽  
Vol 58 (3) ◽  
pp. 871-875
Author(s):  
A. Herberg
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Network Structure ◽  
Fuzzy Systems ◽  
Fuzzy Neural Networks ◽  
Cnc Machining ◽  
Machining Process ◽  
Modeling Process ◽  
Fuzzy Neural ◽  
Takagi Sugeno

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.

Renewable energy selection based on a new entropy and dissimilarity measure on an interval-valued neutrosophic set

2021 ◽  
pp. 1-18
Author(s):  
ShuoYan Chou ◽  
Truong ThiThuy Duong ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Membership Function ◽  
Fossil Fuels ◽  
Multiple Criteria Decision Making ◽  
Clean Energy ◽  
Dissimilarity Measure ◽  
Neutrosophic Set ◽  
Trade Offs ◽  
And Performance

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.

Observer-based proportional derivative fuzzy control for singular Takagi-Sugeno fuzzy systems

2021 ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Wen-Jer Chang ◽  
Ming-Hsuan Tsai ◽  
Yi-Chen Lee
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Systems ◽  
Takagi Sugeno
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