What Is Fuzzy Logic?

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2 Tutorial 'lcclnk' is not recognized as an internal or external command, operable program or batch file. To include the command in the PATH environment variable, type the following in the DOS Command Window: matlabroot\sys\lcc\bin\lcclnk fismain.obj Example — Using the Fuzzy Inference Engine on UNIX Platforms This example demonstrates how to simulate a fuzzy inference system on a UNIX ® platform using the stand-alone fuzzy inference engine. 1 Open a UNIX Command Window and change the directory to matlabroot\toolbox\fuzzy\fuzzy. Tip You can find the root directory of your MATLAB installation by typing matlabroot at the MATLAB command prompt. 2 In the UNIX Command Window, type the following command: cc -O -o fismain fismain.c -lm This command creates the fismain file in the matlabroot\toolbox\fuzzy\fuzzy directory. The fis.c file is included in the fismain.c file;youdonothavetocompile it separately. 3 At the MATLAB prompt, create an input data file using the following command: [x, y] = meshgrid(-5:5, -5:5); input_data = [x(:) y(:)]; save fis_in input_data -ascii 2-168
Simulating Fuzzy Inference Systems Using the Fuzzy Inference Engine This command saves the input data as a 121-by-2 matrix in the ASCII file fis_in in your current working directory. Each row of the matrix represents an input vector. Tip You can find your current working directory in the Current Directory field in the MATLAB desktop toolbar. 4 Copy the FIS structure file mam21.fis from the matlabroot\toolbox\fuzzy\fuzdemos directory to your current working directory. 5 Copy the fismain file from the matlabroot\toolbox\fuzzy\fuzzy directory to your current working directory. 6 In the UNIX Command Window, change the directory to your current working directory, and type the following executable command: fismain fis_in mam21.fis This command uses the data file fis_in and the FIS structure file mam21.fis and generates 121 outputs on your screen. Tip You can also direct the outputs to another file using the following command in the DOS Command Window: fismain fis_in mam21.fis > fis_out This command saves the output data fis_out as a 121-by-1 matrix in your current working directory. Each row of the output matrix represents an output vector. 2-169
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Fuzzy Logic Toolbox 2 User’s Guid
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Revision History January 1995 First
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Overview of Fuzzy Inference Process
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Simulink Environment ..............
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x Contents
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1 Getting Started Product Overview
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1 Getting Started If you just want
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1 Getting Started Another basic con
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1 Getting Started Input Space (all
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1 Getting Started do a fine job wit
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1 Getting Started An Introductory E
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1 Getting Started See how the formu
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1 Getting Started tip=(0.15)*servRa
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1 Getting Started 0.25 0.2 tip 0.15
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1 Getting Started or perhaps rewrit
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2 Tutorial Overview The point of fu
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2 Tutorial Foundations of Fuzzy Log
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2 Tutorial How does it work? Reason
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2 Tutorial One of the most commonly
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2 Tutorial A fuzzy set is an extens
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2 Tutorial Polynomial based curves
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2 Tutorial A B min(A,B) A B max(A,B
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2 Tutorial the fuzzy sets to be com
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2 Tutorial if temperature is cold t
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2 Tutorial Fuzzy Inference Systems
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2 Tutorial Information flows from l
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2 Tutorial selects the maximum of t
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2 Tutorial In the following diagram
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2 Tutorial 1. if and then Interpret
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2 Tutorial Customization Oneofthepr
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2 Tutorial adaptive neural fuzzy in
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2 Tutorial Getting Started We’ll
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2 Tutorial Name of the system. Chan
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2 Tutorial 8 Select File > Export >
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2 Tutorial Editor shares some featu
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2 Tutorial can first use the mouse
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2 Tutorial d Verify that 3 is selec
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2 Tutorial 5 In the FIS Variables a
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2 Tutorial Now that the variables h
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2 Tutorial one of the variable qual
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2 Tutorial A literal interpretation
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2 Tutorial Notice that under food,
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2 Tutorial Upon opening the Surface
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2 Tutorial Building Fuzzy Inference
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2 Tutorial Specifying Custom Member
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2 Tutorial 3 In the FIS Editor, sel
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2 Tutorial Using the custmf1 exampl
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2 Tutorial 6 To add custom membersh
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2 Tutorial In the toolbox, the AND
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2 Tutorial 1 In the lower-left pane
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2 Tutorial Working from the Command
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2 Tutorial The structure.field synt
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2 Tutorial After closing any open M
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2 Tutorial 25 20 tip 15 10 5 10 8 6
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2 Tutorial a.output(1).mf(2).type='
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2 Tutorial All the information for
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2 Tutorial 44. 2 The list of comman
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2 Tutorial Working in Simulink Envi
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2 Tutorial 2 1.8 1.6 1.4 1.2 1 0.8
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2 Tutorial 0.8 0.6 0.4 0.2 valve 0
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2 Tutorial If you stop the simulati
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2 Tutorial FIS. This automatic mode
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2 Tutorial Type slcp attheMATLABpro
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2 Tutorial As the figure shows, the
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2 Tutorial The final output of the
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2 Tutorial the Sugeno-type represen
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2 Tutorial and the membership funct
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2 Tutorial anfis and the ANFIS Edit
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2 Tutorial alone or in combination
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2 Tutorial Constraints of anfis anf
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2 Tutorial You can also load Testin
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2 Tutorial Validating the Trained F
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2 Tutorial The training data appear
Page 148 and 149: 2 Tutorial 1 Choose Grid partition,
Page 150 and 151: 2 Tutorial Viewing Your FIS Structu
Page 152 and 153: 2 Tutorial The plot shows the check
Page 154 and 155: 2 Tutorial • Select the Checking
Page 156 and 157: 2 Tutorial In this case, the checki
Page 158 and 159: 2 Tutorial anfis from the Command L
Page 160 and 161: 2 Tutorial data values. You use the
Page 162 and 163: 2 Tutorial subplot(2,2,4) plotmf(fi
Page 164 and 165: 2 Tutorial Thedifferencebetweentheo
Page 166 and 167: 2 Tutorial As a result, the trainin
Page 168 and 169: 2 Tutorial Output FIS Structure for
Page 170 and 171: 2 Tutorial Output FIS Structure for
Page 172 and 173: 2 Tutorial right location within a
Page 174 and 175: 2 Tutorial Here, the variable cente
Page 176 and 177: 2 Tutorial Finally, plot the two cl
Page 178 and 179: 2 Tutorial The genfis2 function bui
Page 180 and 181: 2 Tutorial fismat=genfis2(datin,dat
Page 182 and 183: 2 Tutorial At this point, you can u
Page 184 and 185: 2 Tutorial The next figure shows th
Page 186 and 187: 2 Tutorial you fit the fuzzy system
Page 188 and 189: 2 Tutorial Plot the checking error
Page 190 and 191: 2 Tutorial information on the clust
Page 192 and 193: 2 Tutorial Saving the Cluster Cente
Page 194 and 195: 2 Tutorial The fis.c file contains
Page 196 and 197: 2 Tutorial This command saves the i
Page 200 and 201: 2 Tutorial 7 To verify that the fuz
Page 202 and 203: 3 Function Reference GUI Tools and
Page 204 and 205: 3 Function Reference FIS Data Struc
Page 206 and 207: 3 Function Reference Simulink Envir
Page 208 and 209: addmf Purpose Syntax Description Ad
Page 210 and 211: addrule Purpose Syntax Description
Page 212 and 213: anfis Purpose Syntax Description Tr
Page 214 and 215: anfis training data set. When you s
Page 216 and 217: anfisedit Purpose Syntax Descriptio
Page 218 and 219: defuzz Purpose Syntax Description D
Page 220 and 221: dsigmf See Also gaussmf, gauss2mf,
Page 222 and 223: evalfis • ORR: the result of eval
Page 224 and 225: fcm Purpose Syntax Description Fuzz
Page 226 and 227: findcluster Purpose Syntax Descript
Page 228 and 229: fuzarith Purpose Syntax Description
Page 230 and 231: fuzzy Purpose Syntax Open basic Fuz
Page 232 and 233: fuzzy Membership functions to invok
Page 234 and 235: gauss2mf See Also dsigmf, gauss2mf,
Page 236 and 237: gbellmf Purpose Syntax Description
Page 238 and 239: genfis1 The default number of membe
Page 240 and 241: genfis2 Purpose Syntax Description
Page 242 and 243: genfis2 Xin1 = 7*rand(50,1); Xin2 =
Page 244 and 245: genfis2 Example 3 The following exa
Page 246 and 247: genfis3 The input membership functi
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genfis3 Example 3 The following exa
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gensurf Example 1 a = readfis('tipp
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getfis 'inlabels' 'outlabels' 'inra
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getfis getfis(a,'input',1) Name = s
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mam2sug Purpose Syntax Description
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mf2mf 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3
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mfedit Selecttheiconforthevariableo
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newfis DefuzzMethod ans = [newsys]
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pimf Purpose Syntax Description Exa
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plotmf Purpose Syntax Description E
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psigmf Purpose Syntax Description B
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mmf Purpose Syntax Description Remo
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mvar Purpose Syntax Description Rem
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uleedit Purpose Syntax Description
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uleview Purpose Syntax Rule viewer
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setfis Purpose Syntax Description S
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sffis Purpose Syntax Description Fu
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showfis 24. average 25. generous 26
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showrule 1. (service==poor) | (food
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sigmf See Also dsigmf, gaussmf, gau
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subclust Purpose Syntax Description
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subclust Examples [C,S] = subclust(
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surfview If you want to create a sm
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trapmf Purpose Syntax Description T
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trimf Purpose Syntax Description Tr
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writefis Purpose Syntax Description
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zmf See Also dsigmf, gaussmf, gauss
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5 Block Reference Controllers Fuzzy
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5 Block Reference Membership Functi
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Diff. Sigmoidal MF Purpose Descript
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Fuzzy Logic Controller with Rulevie
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Gaussian2 MF Purpose Description Co
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Pi-shaped MF Purpose Description Se
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Probabilistic Rule Agg Purpose Desc
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S-shaped MF Purpose Description See
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Trapezoidal MF Purpose Description
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Z-shaped MF Purpose Description See
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A Examples Introductory Examples
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B Bibliography [1] Bezdec, J.C., Pa
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B Bibliography [22] Zadeh, L.A.,
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Glossary fuzzy c-means clustering A
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Glossary Glossary-4
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Index H hybrid method 2-121 I if-th
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What Is Fuzzy Logic?

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