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# Fuzzy Systems - Science topic

Explore the latest questions and answers in Fuzzy Systems, and find Fuzzy Systems experts.

Questions related to Fuzzy Systems

How can I obtain the membership functions associated to sign function in order to design a Takagi-Sugeno fuzzy model? Thank you.

How can i generate the rules matrix of a fuzzy system that has two outputs and the outputs are logically combined using the "and" operator. (In MATLAB envirement)?

p--->q and r

The fuzzy system has 3 rules like above. The membership functions are triangular, and the linguistic variables are "Low", "Medium" and "High".

In his name is the judge

Hi

I have to use tsk fuzzy system in python for my research.

Please recommend me a library for tsk ( not mamdani ) fuzzy system in python.

Also if this library exist please Introduce me a source for learning it in python.

wish you best

Take refuge in the right.

In his name is the judge

Hi

In order to design controler for my damper ( wich is tlcgd), i want to use fuzzy system.

So i have to optimize rules for fuzzy controler. i want to know for optimizition rules of fuzzy systems wich one is the best genetiz algorithm or Artificial neural network?

Wish you best

Take refuge in the right.

I have just designed a fuzzy system, and now I want to redesign it based on the fractional order. However, I have no idea where to start from and what to do. Could you please tell me what I should do and mention any related sources to study?

Are there sources explain how ANFIS code can be generated to optimize it by Particle Swarm Optimization (PSO)?

I am interested to use SAFIS and DENFIS model for my machine learning project. Can anyone help me with the coding or suggest any methods using MATLAB or Python?

We know that, a particular variable may have some inherent sub-domains out of which few of them may be intersecting or non intersecting. If such variable exists in a nonlinear objective function then it is hardly possible to optimize this function. Thus we need to create a unified domain by utilizing such subdomains. Then the function under study can be easily solved. However, we knew that fuzzy system can give an approximated solution of a function which is associated to the variables of impreciseness( non-random uncertainty). Thus using fuzzy system we may create almost nearly an unified domain.

firstly my fuzzy system is based on 5 image features dental x-ray images, consisting of 120 preapical images. features are described as below:

1-Entropy, Edge-Value, and Intensity: [30:55]

2-Local Binary Patterns - LBP: [140:160]

3-Red-Green-Blue - RGB: [82:140]

4-Gradient Feature: [0.3:0.45]

5-Patch Level Feature: [0.01:0.33]

output range: [1:5]

based on the article:

I achieved the membership function parameters of my fuzzy system (the number of my parameters to optimize were 48).

then created a cost function to optimize the values in order to minimize the Errors. but it gained a poor accuracy (about 13%) and a great number of MAE and MSE (MAE=1.27 and MSE= 2.22).

Is there a better.

Do you know a better way to optimize my system?

my programming software: MATLAB2019

what's your opinion about Fuzzy logic future?

do you think Fuzzy logic would be develop like machine learning in nowadays ?

and let's start a discussion about Advanced Application of fuzzy logic and fuzzy systems...

Besides the Schneider Electric PLCs that are programmed with EcoStruxure Control Expert or Unity Pro, Do you know of any other PLC(s) that include fuzzy control functions?

It would be interesting to know which manufacturers have been following the IEC 61131-7 standard, to know the state of the art of the application of fuzzy systems in industrial processes.

Mathematically, it seems neutrosophic logic is more generalized than intuitionistic fuzzy logic. But, when it comes to real life scenarios, I couldn't find any advantage of neutrosophic logic over Intuitionistic fuzzy logic.

Even in some cases, intuitionistic fuzzy logic is seems more logical than neutrosophic logic. Just like the following situations in neutrosophic...

(T, F, I) : (1,0,1), (1,1,0), (1,1,1), (0,0,0), (0,1,1)

seems to be not possible in real life scenario.

Whereas, There is no chance of getting such scenarios in case of Intuitionistic fuzzy logic.

In the study of Duality theory, Nonlinear programming problem, Dual space etc,( particularly on fuzzy system also) we generally see a duality gap appears and this gap varies differently according to the selection of feasible region. So, it is trouble some to get best approximation of the solution of the problem. However, in linear programming problem no duality gap exists .

In fuzzy system, we generally try to measure the qualitative difference of a certain object/ subject. In Physics/ Chemistry discipline there are specific formula to answer the question. But, my point is to get an alternative formula to do the same job via fuzzy system in Applied Mathematics discipline/ soft computing discipline. To tackle with such question the following subtopic may be considered.

Fuzzy logic and Fuzzy set, Degree of fuzziness, Learning experiences, Human perception, Time series analysis

I am working on Power system modles in MATLAB with some adaptive controllers. The simulation run for different time duration like 8,10, and 15 sec. Now i need to get the computational time taken by the computer to solve the iteration behind theses simulations. I found tic and toc command but need more detailed explanation to use it. Thanks

I have prepared one two DOF semi active fuzzy control system with Bouc-Wen model. But Fuzzy system is not working its very slow.

What mistake I am doing or what is wrong with my model.

The model, fis file, and two reference paper are attached with this. What's wrong with the model not clear.

I am working on the

**I have a question, how to select the matrix***Delayed Singular T-S fuzzy systems*.**"E"**for the simulation. Mean its compulsory its values is non-unity or we can put the value unity?Dear all,

I am trying to design an FRBS using Matlab fuzzy logic toolbox. The fuzzy system will be used to predict player's type based on inputs (gameplay data) and a set of rules defined by experts.

I have 6 inputs and 4 outputs (types of players). The given rules do not concern all inputs (specific inputs are used for each player type).

Is it imperative to include all inputs and outputs in a rule? Also is there a min/max of rules that an FRBS should include?

Thank you for your help.

Hi

i'm having a hard time working with Fuzzy toolbox in matlab, i have made a fis, i have added my desired membership functions for input and outputs. Now i want to generate fuzzy rules based on my Data set for input/output. I have 1000 input data and their 1000 output data. what should i do?

this is my code

%% Fuzzy Inference System Definition

MyFuzzySystem=newfis('Amin');

MyFuzzySystem=addvar(MyFuzzySystem,'input','theta',[-40 40]);

MyFuzzySystem=addvar(MyFuzzySystem,'output','x',[0 20]);

MyFuzzySystem=addvar(MyFuzzySystem,'output','y',[0 10]);

%% Adding MFs to the theta input

MyFuzzySystem=addmf(MyFuzzySystem,'input',1,'','trapmf',[-40 -40 -39.2 -38.4]); %A1

for i=2:99

MyFuzzySystem=addmf(MyFuzzySystem,'input',1,'','trimf',[0.8*i-40.8 0.8*i-40 0.8*i-39.2]); %%A2-A99

end

MyFuzzySystem=addmf(MyFuzzySystem,'input',1,'','trapmf',[38.4 39.2 40 40]); %A100

%mfedit(MyFuzzySystem)

%plotmf(MyFuzzySystem,'input',1);

%% Adding MFs to the x output

for i=1:101

MyFuzzySystem=addmf(MyFuzzySystem,'output',1,'','trimf',[0.2*(i-2) 0.2*(i-1) 0.2*(i)]); %%B1-B101

end

%% Adding MFs to the y output

for i=1:101

MyFuzzySystem=addmf(MyFuzzySystem,'output',2,'','trimf',[0.1*(i-2) 0.1*(i-1) 0.1*(i)]); %%C1-C101

end

%mfedit(MyFuzzySystem)

%% Generating Input-Output Data

%%% Generating theta

phi=rand(100,1)*2*pi;

omega=rand(100,1)*50;

theta=zeros(1,1000);

alpha=zeros(100,1000);

for i=1:100

for t=1:1:1000

alpha(i,t)=(((40/sqrt(2))*(sin(omega(i,1)*(t/100)+phi(i,1))+cos(omega(i,1)*(t/100)+phi(i,1)))));

end

end

for k=1:1000

sum_alpha=0;

for w=1:100

sum_alpha=sum_alpha+alpha(w,k);

end

theta(1,k)=sum_alpha/100;

end

subplot(2,2,1);

t=1:1000;

y=(40/11)*theta;

theta_degree=theta*(pi/180);

plot(t/100,y);

xlabel('t');

ylabel('theta(t)');

xlim=[0,10];

ylim=[-40,40];

%%% Calculating phi

b=10;

phi_out(1,1)=45;

for i=1:999

phi_out(1,i+1)=phi_out(1,i)-asin((2*sin(theta_degree(1,i)))/b);

end

subplot(2,2,2);

t=1:1000;

plot(t/100,phi_out);

xlabel('t');

ylabel('phi(t)');

%%% Calculating x(t), y(t)

x_out(1,1)=0;

y_out(1,1)=0;

for i=1:999

x_out(1,i+1)=x_out(1,i)+cos(phi_out(1,i)+theta_degree(1,i))+sin(theta_degree(1,i)).*sin(phi_out(1,i));

y_out(1,i+1)=y_out(1,i)+sin(phi_out(1,i)+theta_degree(1,i))-sin(theta_degree(1,i)).*cos(phi_out(1,i));

end

subplot(2,2,3);

plot(x_out,y_out)

xlabel('x');

ylabel('y');

InputOutputData=[theta' x_out' y_out'];

How to optimize Model predictive controller using machine learning ? e.g. using Neural Network or fuzzy systems

Hi! I have a system that loosely looks like this-

$\dot{x}_{1}=f_{1}(x_{1},x_{2},x_{3},x_{4})$,

$\dot{x}_{2}=f_{2}(x_{1},x_{2},x_{3},x_{4})$,

$\dot{x}_{3}=x_{4}$,

$\dot{x}_{4}=f_{4}(x_{1},x_{2},x_{3},x_{4})+bu_{1}$,

$y=x_{3}$,

I am designing a direct fuzzy adaptive controller to control the state x3. I wish to know what should be inputs to the fuzzy system that will approximate the ideal controller? Is it going to be all the states i.e $x_{1},x_{2},x_{3},x_{4}$ or $e,\dot{e}$? And finally what kind of adaptive law will ensure that the error is driven to zero. In my real system, I have got 9 states, and the state that I am interested in controlling has a relative degree of two. So, Shall I take all the states as input to my adaptive fuzzy controller? If I choose that, then will it not be exhorbitantly computationally expensive- considering the fact that there are 3 MFs per input-- resulting in $3^{9}$ rules? Kindly provide your inputs. Thanks in advance.

Right from the fuzzy number developed by Zadeh (1965), new series of uncertain number are developed by researchers like grey number (Deng 1989), rough number (Zhai et al. 2007), Type-2 fuzzy number (Mendel & John 2002), neutrosophic numbers (Smarandache 2003), Z- number (Zadeh 2011), D-number (Deng 2012), shadowed fuzzy set (Pedrycz 1998).

Recently, in the year 2015-2017, are there any methods developed.

To develop research about modeling the path of the planets by fuzzy systems and artificial neural networks, what methods can be useful?

I need a mathematical equation of the form z= f(x, y) where x's domain is (0,1), y's domain is (0,4), and z must be [0 , 1]. Are there any methodology.

To be more accurate, x is the weight of a fuzzy system, y is the output of this fuzzy system, and z is the final weighted output of this fuzzy system, which will be entered in another process.

I have a fuzzy system with multiple vague parameters represented as fuzzy numbers. I have to simulate the system performance. I am thinking of randomly generating membership grades for these parameters (individually) and find the performance of the system. If I randomly pick a membership grade and find the alpha cut, can it be another fuzzy number ? If it can be treated as another fuzzy number, what will the membership function of it look like?

For instance with three variables and three membership function, 27 rules can produced, but the problem is when you have more than five variables all with three membership functions

A problem requires more than 2000 rules which are difficult even to decide by the experts. So, can we simply use an Orthogonal Array?

- Could you please point me out to some successful Medical sciences applications using partial differential equations?

- Preferably, involving heat, reaction-diffusion, Poisson, or Wave equation.

- If possible in fuzzy environment.

Best regards

Sarmad.

What is the Necessary and sufficient conditions for using the Fuzzy systems and when we cant use this theory?

How to implement Interval typre2 Fuzzy system in Matlab Simulation.

How to add Matlab toolbox?

How to implement interval type2 fuzzy system in Matlab Simulation?

Is there is any Type2 fuzzy system in Matlab?

This type of algorithm (Takagi-Sugeno fuzzy) is talent to deal with MIMO plants that possess lag time, big inertia and uncertainty and can be deemed as one of the most important components of intelligent buildings

which defuzzification method is more suitable for triangular fuzzy numbers considering their shape, height, relative location and spread?

I must write Sugeno type fuzzy controller with .m script. How can I write without using fuzzy toolbox? Where can I find an example about it?

Thanks...

How large or How small the values of scale factors can be set to assure that the fuzzy logic control performance will not be affected?

I have a project to develop the application of fuzzy logic / fuzzy set theory to pictures made by patients and in psychotherapy more generally such as recovery and diagnosis.

By providing dependent variable and independent variables in fuzzy, How get the solution using fuzzy logic ?

I want to create a membership function for the probability distribution (generated from statistical data) of the remaining fatigue life. Can anybody guide me on how to do so? I have found few papers on internet but most of these seem to confuse me rather than helping me. It would be great if somebody could guide me in the aforementioned matter. Thanks.

Dear researchers,

Please help me out to learn about the fuzzy system from the scratch.

Please guide me with the steps and resources to follow .

Thanking you,

With regards,

Bhaskar Ghosh

I m working on use of fuzzy logic in water quality indezing...

I would like to implement type 2 fuzzy controller system on FPGA . Which FPGA module is best to implement for real time Type 2 Fuzzy Logic System for Control System Applications?

I want to compare proposed measure of directed divergence with some existing measure,a research paper states that since it depict the minimization of degree of difference, directed divergence is better. Why? Refer attached file

If I am designing a fuzzy Logic system and one of the input variables is with two levels:

Low: having the range ( 0-2)

High: having the range (3-5)

If I am designing two membership functions to represent the two levels of the variable using a trapezoidal type, are the bellow values correct to form the trapezoidal:

Low: [ 0 0 1 2 ]

High: [ 1 3 5 5 ]

If not, how can I consider the overlap area from the above mentioned ranges?

Thanks,

I want to use fuzzy DEA and I haven't found any solver handled this kind of problem, that's why I have written my own program. How can I learn to easily write my DEA program to MATLAB or AMPL?

Suppose the two traingular fuzzy numbers A=(a1,b1,c1) and B=(a2, b2, c2). The subtraction operator "(-)" can be implemented by the following formula: A(-)B=(a1-a2, b1-b2, c1-c2). There may occur some dilemmas if (b1-b2)>(c1-c2) or (a1-a2)>(b1-b2). So are there any improvements can be explored to deal with this matter? Or are there some specific distance concepts can be used to reflect the subtraction operation?

Thanks very much for your attention and advice.

i am working on fault detection of a suspension system using fuzzy. problem is i have to convert my model (differential equations) into space space form. but in which form i can convert it ? need any paper or stuff that can help me understand how i can do it all. i want to implement multiple fuzzy models for fault detection.

The system is nonlinear described by a set of 8 ODEs (8 states). Two discontinuous functions (jump discontinuity) are present in the first state equation. Can any one suggest the method to design a TS fuzzy model for such system?

dx1/dt = -x1.x3 + k12.x2 + EGP(1 - x5) - F - Fr + u1

dx2/dt = x1.x3 - k12.x2 - x2.x4

dx3/dt = -ka1.x3 + kb1.x6

dx4/dt = -ka1.x4 + kb1.x6

dx5/dt = -ka1.x5 + kb1.x6

dx6/dt = -ke.x6 + ki.x7

dx7/dt = -ki.x7 + ki.x8

dx8/dt = -ki.x8 + u2

states: [x1 x2 x3 x4 x5 x6 x7 x8]

parameters: [k12 EGP ka1 ka2 ka3 kb1 kb2 kb3 ki ke]

dis-continuous functions: [1] Fr = 0.003(x1-9), when x1>=9

Fr = 0, [otherwise]

[2] F = 0.97 , when x1>=4.5

F = 0.97.x1/4.5 [otherwise]

Q/ How to take the discontinuous functions as premise variables of fuzzy model?

How to get the values of parameters of pimf from dataset?

Like pimf(x, [a b c d]) or another pimf(x, C, lambda), C is centre and lambda>0 is the scaling factor. How can I calculate the value of lambda?

I would be grateful if you could send me the download link of it, because I could not find it via internet while I really need it. There is interval type2 fuzzy toolbox but I could not find Generalized fuzzy toolbox.

i want to create two types of chromosomes based on different criteria. The first type is based on job length,the CPU speed of the resources,and the RAM size of the resources. The second type is based on the job length and the bandwith of the resources.These criteria are the input parameters for the fuzzy system.

I have Input and output data set and going for modelling. I am getting negative values of output from ANFIS model but in training as well as testing input there is no negative value. Tell me how to solve this problem.

I am new to Fuzzy logic. I created membership functions with some rules by using matlab Fuzzy Logic Toolbox. Now i want to train this mamdani fuzzy model Can any body help ?

you can see Rule view.

Identification of societal problems which are related to fuzzy dynamical systems and suitable techniques for solving them.

I want to determine the fuzzy intervals in a medical fuzzy system but physicians who consult to me do not have any view about fuzzy decisions . They say me "according our medical references , anything is crisp and based on discrete values" . I disappointed from their helps and now want to determine this fuzzy MFs based on clinical guidelines and aome experiences in medicine. Is there a machine learning or wizard or default and simple and basic method to determine these parameters ? I want a scientific approach if exists ?!

In the event of borrowing the concept of fuzzy soft set into ontology so as to reason with the uncertain concepts of a domain, I discover fuzzy soft set is best used in making comparison among instances (objects) and then the optimal decision could be reached using the score values of those objects. But what happens when am only concern about the truthfulness of a particular object in the domain, must I also have to make comparison with other objects in that domain? Also how best can I handle the binary relationships that exist between the object of concern and other objects in the domain

can any one provide me any material for understanding or code of Optimal Completion Strategy in Fuzzy k Nearest Neighbour

Dear all,

I am working with an ANFIS (adaptive neuro-fuzzy) model (genfis1) using grid partitioning. I would like to know the time complexity in terms of Big O of an ANFIS. I am also wondering how can we decide a complexity of a multi-layered perceptron (MLP) neural network?

As the title,How can I train some zero-order TSK fuzzy systems with the same antecedents and same input MFs? Obviously,these zero-order TSK fuzzsy systems have different consequent parameters.

I hold the idea that it is impossibile to obtain different zero-order TSK fuzzy systems with the same antecedent and input MFs.

Are there some solutions?thank you!!!

In the fuzzy system,once we fix the input variables and corresponding to MFs, are the rules of the fuzzy system been fixed?For example ,threre are 2 input variables and corresponding to 4 MFs in each input. So how many rules in total, 8 or 16? And I have some findings in a paper of ANFIS presented in the picture? I want to know why is that? Thanks a lot!!!

i referred some books and journals they dealing with only two para meters, kindly clarify my doubt .

Hi

I am using a Sugeno fuzzy system to represent a controller for a non linear system. The input of the system is a current feedback measurement across the load (RLC load) and the output to the system is a biphasic DC voltage.

One of my colleague ask if I can show proof that the system is stable under the fuzzy controller.

Is there exist a simple proof for this?

Thank you

I finished my M.Sc. in Chalmers Unvesity in Sweden and have two ISI indexed publication. I have a good knowledge of decision making. My last paper about Decision Making accepted in on of springer journals.

Note that the current paper which I want to co-auther it is half ready.

I am looking for somebody with PhD degree or higher who can comment on it and be a second author.

I want to measure the quality of a fuzzy clustering algorithms, and I need a reliable measure to do this.

I designed a controller to the cable-driven robot, and get a group of

**parameter Q，**based on*r*and ᵨ*cut-and-try method*. The original parameter Q，r and p taken from a paper on IEEE transaction on fuzzy system. I try to find the best parameter Q，r and p for our controller although the cut-and-try method does works in Riccati-like equation(1).PA + ATP – 2/rPBBTP + I/ᵨ2 PBBTP=0 (1)

Kindly suggest me some related resources.