Energy reliability in macro base stations: A feasible solution based on a type-1 Mamdani fuzzy system

2021 ◽  
Vol 195 ◽  
pp. 107126
Author(s):  
Caique R. Miranda ◽  
Fabrício P. V. de Campos ◽  
Moisés V. Ribeiro
Keyword(s):  
Fuzzy System ◽  
Feasible Solution ◽  
Base Stations ◽  
Energy Reliability

On interval-data based Type-1 Takagi-Sugeno fuzzy systems for uncertain nonlinear dynamic system identification

2016 ◽  
Vol 64 (6) ◽  
Author(s):  
Salman Zaidi ◽  
Andreas Kroll
Keyword(s):  
Fuzzy System ◽  
Nonlinear Dynamic ◽  
Nonlinear Dynamic System ◽  
Random Variable ◽  
Interval Data ◽  
Fuzzy Modelling ◽  
Symbolic Data ◽  
Specific Assumption ◽  
Takagi Sugeno

AbstractA novel interval-data based Takagi-Sugeno fuzzy system is proposed to identify uncertain nonlinear dynamic systems by endowing the classical TS fuzzy system with probability theory and symbolic data analysis. Such systems have variability in their outputs, that is they produce varying responses each time when the same stimuli is applied to them under the same condition. Interval data is generated by repeating the identification experiment multiple times and applying the probabilistic techniques to get soft bounds of output. The interval data is then directly used in the TS fuzzy modelling, giving rise to interval antecedent and consequent parameters. This method does not require any specific assumption on the probability distribution of the random variable that models the uncertainty. The developed procedure is demonstrated for a pneumatic drive system.

scholarly journals Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System

2012 ◽  
Vol 2012 ◽  
pp. 1-27 ◽  
Author(s):  
Ll Yi-Min ◽  
Yue Yang ◽  
Li Li
Keyword(s):  
Fuzzy Control ◽  
Fuzzy System ◽  
External Disturbance ◽  
Approximation Error ◽  
Adaptive Backstepping ◽  
Control Approach ◽  
Type Reduction ◽  
Adaptive Laws

A novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced by the average of two type-1 fuzzy systems. Ultimately, the adaptive laws, by means of backstepping design technique, will be developed to adjust the parameters to attenuate the approximation error and external disturbance. According to stability theorem, it is proved that the proposed Type-2 Adaptive Backstepping Fuzzy Control (T2ABFC) approach can guarantee global stability of closed-loop system and ensure all the signals bounded. Compared with existing Type-1 Adaptive Backstepping Fuzzy Control (T1ABFC), as the advantages of handling numerical and linguistic uncertainties, T2ABFC has the potential to produce better performances in many respects, such as stability and resistance to disturbances. Finally, a biological simulation example is provided to illustrate the feasibility of control scheme proposed in this paper.

scholarly journals Comparative Study of Type-1 and Type-2 Fuzzy System in Decision Support System

2018 ◽  
Vol 6 (3) ◽  
Author(s):  
Humaira Humaira ◽  
Yance Sonatha ◽  
Cipto Prabowo ◽  
Hidra Amnur ◽  
Rita Afyenni
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Comparative Study ◽  
Support System ◽  
Fuzzy System

scholarly journals Comparison of Type-1 and Type-2 Fuzzy Systems for Mineralization of Bioprinted Bone

2021 ◽  
Author(s):  
Ashkan Sedigh ◽  
Mohammad-R. Akbarzadeh-T ◽  
Ryan E. Tomlinson
Keyword(s):  
Fuzzy System ◽  
Fuzzy Systems ◽  
Approximation Error ◽  
Culture Period ◽  
Biological Parameters ◽  
High Uncertainty ◽  
Pressure Nozzle

ABSTRACTBioprinting is an emerging tissue engineering method used to generate cell-laden scaffolds with high spatial resolution. Bioprinting parameters, such as pressure, nozzle size, and speed, have a large influence on the quality of the bioprinted construct. Moreover, cell suspension density, cell culture period, and other critical biological parameters directly impact the biological function of the final product. Therefore, an approximation model that can be used to find the values of bioprinting parameters that will result in optimal bioprinted constructs is highly desired. Here, we propose type-1 and type-2 fuzzy systems to handle the uncertainty and imprecision in optimizing the input values. Specifically, we focus on the biological parameters, such as culture period, that can be used to maximize the output value (mineralization volume). To achieve a more accurate approximation, we have compared a type-2 fuzzy system with a type-1 fuzzy system using two levels of uncertainty. We hypothesized that type-2 fuzzy systems may be preferred in biological systems, due to the inherent vagueness and imprecision of the input data. Here, our results demonstrate that the type-2 fuzzy system with a high uncertainty boundary (30%) is superior to type-1 and type-2 with low uncertainty boundary fuzzy systems in the overall output approximation error for bone bioprinting inputs.

scholarly journals Uncertainty Avoider Interval Type II Defuzzification Method

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Sadegh Aminifar
Keyword(s):  
Fuzzy System ◽  
Uncertainty Avoidance ◽  
System Response ◽  
Type Reduction ◽  
Meaningful Relationship ◽  
System Output ◽  
Computational Bottleneck ◽  
Interval Type

One of the IT2FS (interval type-2 fuzzy system) defuzzification methods uses the iterative KM algorithm. Because of the iterative nature of KM-type reduction, it may be a computational bottleneck for the real-time applications of IT2FSs. There are several other interval type-2 defuzzification methods suffering from lack of meaningful relationship between membership function uncertainties and changing of system output due to lack of clearly defined variables related to uncertainty in their methods. In this paper, a new approach for IT2FS defuzzification is presented by reconfiguring interval type-2 fuzzy sets and how uncertainties are present in them. This closed-formula method provides meaningful relation between the presence of uncertainty and its effect on system output. This study investigates uncertainty avoidance that the output of IT2FS obtained by centroid or bisection methods in comparison with type-1 fuzzy system (T1FLS) moves to points with less uncertainty. Uncertainty can enter into T1FSs and affect system response. Finally, for proving the affectivity of the proposed defuzzification method and uncertainty avoidance, several investigations are done and a prototype two-input one-output IT2FS MATLAB code is enclosed.

scholarly journals Estimation of Food Security Risk Level UsingZ-Number-Based Fuzzy System

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Rahib H. Abiyev ◽  
Kaan Uyar ◽  
Umit Ilhan ◽  
Elbrus Imanov ◽  
Esmira Abiyeva
Keyword(s):  
Food Security ◽  
Fuzzy Sets ◽  
Fuzzy System ◽  
Risk Level ◽  
Uncertain Information ◽  
Security Risk ◽  
Fuzzy Logic Systems ◽  
Reliability Parameters ◽  
Basic Parameters

Fuzzy logic systems based on If-Then rules are widely used for modelling of the systems characterizing imprecise and uncertain information. These systems are basically based on type-1 fuzzy sets and allow handling the uncertain and imprecise information to some degree in the developed models. Zadeh extended the concept of fuzzy sets and proposedZ-number characterized by two components, constraint and reliability parameters, which are an ordered pair of fuzzy numbers. Here, the first component is used to represent uncertain information, and the second component is used to evaluate the reliability or the confidence in truth.Z-number is an effective approach to solving uncertain problems. In this paper,Z-number-based fuzzy system is proposed for estimation of food security risk level. To construct fuzzy If-Then rules, the basic parameters cereal yield, cereal production, and economic growth affecting food security are selected, and the relationship between these input parameters and risk level are determined through If-Then fuzzy rules. The fuzzy interpolative reasoning is proposed for construction of inference mechanism of aZ-number-based fuzzy system. The designed system is tested using Turkey cereal data for assessing food security risk level and prediction periods of the food supply.

scholarly journals Comparative Study of Type-1 and Type-2 Fuzzy System in Decision Support System

2018 ◽  
Vol 6 (3) ◽  
Author(s):  
Humaira Humaira ◽  
Yance Sonatha ◽  
Cipto Prabowo ◽  
Hidra Amnur ◽  
Rita Afyenni
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Comparative Study ◽  
Support System ◽  
Fuzzy System

scholarly journals A Simple and Efficient Algorithm for Solving Type-1 Intuitionistic Fuzzy Solid Transportation Problems

2018 ◽  
Vol 9 (3) ◽  
pp. 90-122 ◽  
Author(s):  
P. Senthil Kumar
Keyword(s):  
Transportation Problem ◽  
Feasible Solution ◽  
Real Life ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Number ◽  
Basic Feasible Solution ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy ◽  
Triangular Intuitionistic Fuzzy Number

This article describes how in solving real-life solid transportation problems (STPs) we often face the state of uncertainty as well as hesitation due to various uncontrollable factors. To deal with uncertainty and hesitation, many authors have suggested the intuitionistic fuzzy (IF) representation for the data. In this article, the author tried to categorise the STP under uncertain environment. He formulates the intuitionistic fuzzy solid transportation problem (IFSTP) and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The STP has uncertainty and hesitation in supply, demand, capacity of different modes of transport celled conveyance and when it has crisp cost it is known as IFSTP of type-1. From this concept, the generalized mathematical model for type-1 IFSTP is explained. To find out the optimal solution to type-1 IFSTPs, a single stage method called intuitionistic fuzzy min-zero min-cost method is presented. A real-life numerical example is presented to clarify the idea of the proposed method. Moreover, results and discussions, advantages of the proposed method, and future works are presented. The main advantage of the proposed method is that the optimal solution of type-1 IFSTP is obtained without using the basic feasible solution and the method of testing optimality.

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