Practical Introduction to Fuzzy Logic with Matlab

In this lecture we review the Fuzzy Logic and see where it is useful. As you might already know, computers can only process information in the binary format that includes 0 and 1. It means that if you want to communicate with the computer, you need to learn code. Also, the program you write will later be translated into something called hardware level code that is understandable by machines as it contains only 0s and 1s. Although the binary system is perfect for machines, it is far from convenient for humans. Look at this example, imagine you want to tell your friend about the large yellow shirt you have bought recently. In order to describe these characteristics to a computer, you need to define variables such as Large, Yellow, and shirt in the binary format. Well, for those of you who are familiar with programming, the solution is to define variables and containers for adjectives like Yellow and nouns like shirts. Although the binary system is perfect for machines, it is not really suitable for us as humans.

This video explains the need and necessity of Fuzzy logic in describing the physical systems that are around not indeed following a classical control model.

In this lecture we see how a simple tipping problem can become a complex and complicated coding problem when we choose to use the conventional control instead of Fuzzy Logic. We will develop a conventional controller using Matlab and make some modifications to the code to see how easy it is to solve a simple problem using piece wise function. Finally, we will solve the same problem using Fuzzy logic method and using Matlab FIS and Fuzzy toolbox. Then we will see how easy and convenient it would be to use Fuzzy Logic vs classic control in this and similar projects.

In this lecture we will introduce the concept of membership functions and lists and how they interact with each other. We get to know different shapes of membership functions

In this lecture we learn how important the membership functions are and we investigate one on a house pricing to make sure we are confident about the concepts it provides.

This lecture explains what a fuzzy support is and why we need to learn these concepts in solving advanced and complex problems.

In this lecture we will learn the concepts of height and cross over in Fuzzy.

In this video we will review the answer to the quiz and cover the choices together.

In this lecture we will learn more about the membership functions and how many types of membership functions are available. Then, we proceed to create our first Matlab fuzzy function.

Write a code for this

Divide space between -11<x<13 linearly with 0.5. Create a triangular function in MATLAB using trimf function Trimf should have these parameters.

a = -9 , b = -1, c= 10

This lecture provides the solution to the project 1 to create the triangular function

We learn how to define fuzzy trapezoidal function in Matlab and how to write some engineering code in Fuzzy

We learn what is the membership function of a Gaussian function looks like and how we can create one in Matlab.

In this lecture we review the classical set characteristics and the relationships between sets

In this video we learn what are the unions and intersection on fuzzy sets

In this short assignment, you are required to find the complement on a graph for a fuzzy set.

In this lecture we will review the solution of the homework together.

We learn how to represent the fuzzy logic membership functions in discrete and continuous manner.

In this lecture we review how to represent functions and set properties on fuzzy membership functions

We solve two examples of complement for sugengo and yager. Matlab code is attached

In this lecture we review a fuzzy logic medical exam regarding the blood pressure and age

In this video we explore one example for summation in fuzzy logic and how two different fuzzy sets can be summed together and we find a new membership function

In this lecture we will implement a discrete fuzzy summation by using Matlab programming. We define boundaries and the membership functions and then create a Matlab code that will do the calculations automatically.

In this video we will learn how to create and implement a continuous fuzzy function (summation) in Matlab environment and then we graph the result in multiple views.

In this lecture I have provided more resources for you to learn plotting techniques in Matlab

This is an additional Lecture on how to use Matlab Plotting Commands - Subplots and Hold

This is an additional Lecture on how to use Matlab Plotting Commands - Additional Properties of Graphs and Plots in Matlab

In this lecture we learn how to work with Matlab Axis and Plot customization

In this video we learn how to do fuzzy approximations using a matlab code and example

One of the fundamentals of any fuzzy logic system are linguistic variables. In this lecture we learn how to define fuzzy linguistic variables systematically.

In this lecture we learn how the physical variables around us are translated to fuzzy variables and how the inference system will use them to make calculations

In this video we will explore the fuzzy decision making and fuzzy logic rules that makes the process much easier.

In this lecture we learn what rule based systems are and what we should do if we do not have enough information about the systems and might miss a series of rules

We will start working with Matlab Fuzzy Logic Designer Toolbox

In this video we will learn how to create rules in Matlab fuzzy logic designer and review the fuzzy surface

In this lecture we learn how defuzzification process works and how we can adjust parameters to get the most optimized result.

In this video we will review the tipping problem that we reviewed earlier both with and without fuzzy logic. This is going to be the first one without fuzzy logic. In the next video we will do the same using fuzzy logic

Paper on Fuzzy Logic Design for a Fluidized Catalytic Cracking Unit

Matlab Fuzzy Logic Toolbox with description of the commands and lots of examples