Fuzzy Logic - A practical introduction
4.1 (7 ratings)
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Fuzzy Logic - A practical introduction

A comprehensive introduction that can have you up-and-running with your first Fuzzy Logic system within minutes.
4.1 (7 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
36 students enrolled
Created by Mr Petrus Rohland
Last updated 3/2017
English
Curiosity Sale
Current price: $10 Original price: $20 Discount: 50% off
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Includes:
  • 33 mins on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Design and implement a Fuzzy Logic inference system.
  • Select appropriate Fuzzy Inference System Type (Takagi-Sugeno VS Mamdani).
  • Create fuzzy rule base from heuristics / expert knowledge.
  • Select fuzzification, inference and defuzzification methods.
  • Fault-find / analyse final Fuzzy system.
  • Identify opportunities for application performance enhancement using Fuzzy Logic.
View Curriculum
Requirements
  • Basic math and graphing.
  • Desire to use Fuzzy Logic to solve problems.
  • Some MS Excel or Google sheets experience would help.
Description

This course is intended for hackers, hobbyists and professionals alike; Anyone that wants to get up-and-running quickly with a Fuzzy inference engine. If you have little or no knowledge of Fuzzy Logic, then this course is definitely for you!

At most you will require basic math skills and access to Google Sheets along with a willingness to use Fuzzy Logic to solve a problem.

I will walk you through the complete design process of a Fuzzy Controller or Inference system - From fuzzification to inference methods up to and including defuzzification. 

This course will have you implementing your first Fuzzy System to solve your real world problem in a little more than half an hour. 

This course is succinct yet comprehensive - It covers each aspect in enough detail to serve as a foundation but not so deep that you get bogged down in the details; it teaches you the lion's share...

 

Who is the target audience?
  • Hackers, hobbyists and professionals with little or no knowledge of Fuzzy Logic.
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Curriculum For This Course
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Introduction and Overview
2 Lectures 02:40

Introduction to course including target student and prior knowledge. An overview on the course is also provided.

Preview 01:02

This lecture provides some background on Fuzzy Logic. You will be able to spot suitable application opportunities for fuzzy logic after watching this clip.

Preview 01:38
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Fuzzy Inference Systems
5 Lectures 19:09

The big picture / block diagram of a typical Fuzzy system with an inference engine is discussed.

Bird's eye view of a Fuzzy Inference System
00:55

Fuzzification techniques are discussed; Different membership functions with their respective equations for calculating a degree of membership are introduced.

Preview 06:36

Provide the equations for calculating the degree of membership of the input to the membership functions.

Degree of Membership Function equations
1 question

Typical inferencing techniques used in Fuzzy Logic are discussed along with creating a fuzzy rule base.

Fuzzy Rule Base and Fuzzy Inference
04:12

A detailed inference example where the fuzzy output from several rules are calculated in order to aid understanding of Fuzzy inference principles.

Example: Fuzzy output from rule base
04:24

Defuzzification techniques are introduced through which crisp output(s) are derived from the fuzzy output variables.

Defuzzification
03:02
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Design Examples
4 Lectures 11:09

The design of the Fuzzy system implemented in Google Sheets is motivated at the hand of engineering/system trade-offs.

Preview 02:47

The implementation in Google Sheets is discussed including a line-by-line explanation of the code.

Design Implementation in Google Sheets
02:34

The worked examples provided in the spreadsheets of the previous lectures are discussed. This lecture is core to building the Fuzzy design understanding.

Worked Examples
04:00

Concluding remarks and recommended practice. 

Conclusion
01:48
About the Instructor
Mr Petrus Rohland
4.1 Average rating
7 Reviews
36 Students
1 Course
Engineer, Entrepreneur, Educator

Petrus Rohland obtained his bachelor's degree in electrical and electronic engineering in 2007. He is a Jack of all trades with an eclectic work history that spans a decade. Multi-disciplinary collaboration is a hallmark of his experiences which include research and development in the defense and maritime industries. His interests are as varied as his work experiences but computational intelligence and control systems are the most prominent contenders.