Scribd
Upload
60 views2 pages

Mahendra Engineering College: Lecture Handouts

This document provides a lecture summary on TSK models. It introduces TSK (Takagi-Sugeno-Kang) fuzzy models, which use fuzzy rules with crisp outputs rather than fuzzy outputs. The lecture discusses the two major types of fuzzy rules - Mamdani and TSK rules. It explains that TSK fuzzy models are used to design TSK fuzzy controllers for nonlinear systems by constructing fuzzy models through either identification using input-output data or derivation from given nonlinear system equations using a two-part procedure of structure identification and parameter identification.

Uploaded by

SHAIK ROSHAN
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOC, PDF, TXT or read online on Scribd
60 views2 pages

Mahendra Engineering College: Lecture Handouts

This document provides a lecture summary on TSK models. It introduces TSK (Takagi-Sugeno-Kang) fuzzy models, which use fuzzy rules with crisp outputs rather than fuzzy outputs. The lecture discusses the two major types of fuzzy rules - Mamdani and TSK rules. It explains that TSK fuzzy models are used to design TSK fuzzy controllers for nonlinear systems by constructing fuzzy models through either identification using input-output data or derivation from given nonlinear system equations using a two-part procedure of structure identification and parameter identification.

Uploaded by

SHAIK ROSHAN
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOC, PDF, TXT or read online on Scribd
You are on page 1/ 2

L-31

MAHENDRA ENGINEERING COLLEGE


MAHENDHIRAPURI, MALLASAMUDRAM - 637503
Dept.EIE VI/III

Lecture Handouts
Subject Name : NEURAL NETWORK AND FUZZY LOGIC CONTROL

Staff Name : ABIRAMI.A AP/ECE

Unit : IV (FUZZY LOGIC FOR MODELING)

Topic of Lecture: TSK MODEL


Introduction :
 A fuzzy controller or model uses fuzzy rules, which are linguistic if-then
statements involving fuzzy sets, fuzzy logic, and fuzzy inference.
 Fuzzy rules play a key role in representing expert control/modeling
knowledge and experience and in linking the input variables of fuzzy
controllers/models to output variable (or variables).
Prerequisite knowledge for Complete learning of Topic:
Boolean algebra,
Rule antecedent and Rule consequent.
Detailed content of the Lecture:
 Two major types of fuzzy rules exist, namely,
 Mamdani fuzzy rules and Takagi-Sugeno (TS, for short) fuzzy rules.
 To design a T-S fuzzy controller, T-S fuzzy model for a nonlinear system.
 Therefore the construction of a fuzzy model represent an important and
basic procedure in this approach.
In general there are two approaches for constructing fuzzy models:
1. Identification (fuzzy modeling) using input-output data and
2. Derivation from given nonlinear system equations.
 The procedure mainly consist of two parts: structure identification and
parameter identification.
TSK model
Linguistic rules

Video Content / Details of website for further learning (if any):


https://www.staff.ncl.ac.uk/damian.giaouris/pdf/IA%20Automation/TS%20FL%20tutorial
Important Books/Journals for further learning including the page nos.:
Fuzzy logic with engineering Applications,” Third Edition” Timothy. J. Ross Pg:no:152-155.

Subject Teacher

Verified by HOD

You might also like