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A REPORT ON FUZZY TOOLBOX IN MATLAB
  AND DESIGNING IT FOR TEMPRATURE
             CONTROL.




                               SUBMITTED BY:-
                   DHRUBA JYOTI BORA(ED012003)
                   SUSMITA KAUSHIK(EDO12004)
                   RHITTWIKRAJ MODGULYA(EDO12005)
                   PIYUSH KANT(EDO12007)

                   BIOELECTRONICS –IInd semester
fuzzy toolbox: The Fuzzy Logic Toolbox provides GUIs to let us perform classical fuzzy system
development. Using the toolbox, we can:
▪ Develop and analyze fuzzy inference systems
▪ Develop adaptive neurofuzzy inference systems
▪ Perform fuzzy operation.

Membership Function Editor: Lets you display and edit the membership functions associated
                                    -
with the input and output variables of the FIS
                                           FIS.

Rule Editor: - Lets you view and edit fuzzy rules using one of three formats: full English
                                                                                   English-like syntax,
concise symbolic notation, or an indexed not
                                         notation.

Rule Viewer: Lets you view detailed behavior of a FIS to help diagnose the behavior of specific
               -

rules or study the effect of changing input variables

Modeling Using Fuzzy Logic:
Firstly we have to go to fuzzy tool box there are two methods for that we can browse the MATLAB
toolbox or just type fuzzy into the command window.

DESIGN ASPECTS OF FUZZY LOGIC CONTROLLE
                              CONTROLLER
Various steps in designing fuzzy logic control system are the following
Step 1 : Define the inputs and outputs for the fuzzy logic control system.
Step 2 : Set up fuzzy membership functions for the input.
Step 3 : Set up fuzzy membership functions fo the output.
                                             for
Step 4: Create a fuzzy rule base.
Step 5: Defuzzify the outputs.

Fuzzy toolbox window shown below:
Membership function editing: Here in this block of the toolbox we are required to edit the
predefined values of the fuzzy membership functions (Input and output depending upon their range.
Rule Editing: Every FIS has some rules that define the behavior of fuzzy output for different fuzzy
inputs. In rule editor we link input membership function to the output membership function and the
perator (and/or) that governs the mechanism of the output of the fuzzy FIS system.




RULE VIEWER: Here in rule viewer we can input different values of input and output’s validity
                                                                            output
based on the FIS rules.

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Report on fuzzy

  • 1. A REPORT ON FUZZY TOOLBOX IN MATLAB AND DESIGNING IT FOR TEMPRATURE CONTROL. SUBMITTED BY:- DHRUBA JYOTI BORA(ED012003) SUSMITA KAUSHIK(EDO12004) RHITTWIKRAJ MODGULYA(EDO12005) PIYUSH KANT(EDO12007) BIOELECTRONICS –IInd semester
  • 2. fuzzy toolbox: The Fuzzy Logic Toolbox provides GUIs to let us perform classical fuzzy system development. Using the toolbox, we can: ▪ Develop and analyze fuzzy inference systems ▪ Develop adaptive neurofuzzy inference systems ▪ Perform fuzzy operation. Membership Function Editor: Lets you display and edit the membership functions associated - with the input and output variables of the FIS FIS. Rule Editor: - Lets you view and edit fuzzy rules using one of three formats: full English English-like syntax, concise symbolic notation, or an indexed not notation. Rule Viewer: Lets you view detailed behavior of a FIS to help diagnose the behavior of specific - rules or study the effect of changing input variables Modeling Using Fuzzy Logic: Firstly we have to go to fuzzy tool box there are two methods for that we can browse the MATLAB toolbox or just type fuzzy into the command window. DESIGN ASPECTS OF FUZZY LOGIC CONTROLLE CONTROLLER Various steps in designing fuzzy logic control system are the following Step 1 : Define the inputs and outputs for the fuzzy logic control system. Step 2 : Set up fuzzy membership functions for the input. Step 3 : Set up fuzzy membership functions fo the output. for Step 4: Create a fuzzy rule base. Step 5: Defuzzify the outputs. Fuzzy toolbox window shown below:
  • 3. Membership function editing: Here in this block of the toolbox we are required to edit the predefined values of the fuzzy membership functions (Input and output depending upon their range.
  • 4. Rule Editing: Every FIS has some rules that define the behavior of fuzzy output for different fuzzy inputs. In rule editor we link input membership function to the output membership function and the perator (and/or) that governs the mechanism of the output of the fuzzy FIS system. RULE VIEWER: Here in rule viewer we can input different values of input and output’s validity output based on the FIS rules.