The Fuzzy block in RecurDyn/CoLink loads the FIS file and executes the Fuzzy logic controller defined in the FIS file. The FIS file can be created either by using MATLAB® or by using a simple text-editor. In this section, the FIS file format is explained so that the user can create a FIS file using any text-editor application.
The FIS file format in RecurDyn/CoLink adopts the fuzzy file format used in Fuzzy Logic Toolbox in MATLAB® package. If the user is familiar with the FIS file format used in the Fuzzy logic controller in MATLAB® package, the user can skip this section.
•FIS file format
File extension of the FIS file is '-.fis'.
The FIS file contains all the necessary information to describe the Fuzzy logic controller and it includes:
•Type of Fuzzy logic
•Control inputs including input Fuzzy membership functions
•Control outputs including output Fuzzy membership functions
•Fuzzy rules
•Types of Fuzzy operation method
•A FIS file consists of 4 sections
•Fuzzy system information ( [system])
This section needs to start with section indicator, [System], at the beginning of the section. In this section, the overall properties of the fuzzy logic controller are defined.
o Name: Name of the Fuzzy controller system. A string value. Write the values between single-quotation marks (' ').
Syntax: Name=‘name_of_the_fuzzy_controller’
o Type: Type of fuzzy interference method to be used. A string value. Either 'mamdani' or 'sugeno'.
Syntax: Type = ‘mamdani’ OR Type= ‘sugeno’
o NumInputs: Number of inputs. An integer number.
Syntax: NumInputs = an_integer
o NumOutputs: Number of outpus. An integer number.
Syntax: NumOutputs = an_integer
o NumRules: Number of fuzzy rules to be defined and used. An integer number.
Syntax: NumRules = an_integer
o AndMethod: The method to be used for AND operation. A string value. Either 'min' or 'prod'.
Syntax: AndMethod = ‘min’ OR AndMethod= ‘prod’
o OrMethod: The method to be used for OR operation. a string value. Either 'max' or 'probor'.
Syntax: OrMethod = ‘max’ OR OrMethod = ‘probor’
o ImpMethod: Implementation method: a string value. Either 'min' or 'prod'
Syntax: ImpMethod = ‘min’ OR ImpMethod = ‘prod’
o AggMethod: Aggregation method: a string value. Either 'max' or 'sum' or 'probor'.
Syntax: AggMethod = ‘max’ OR AggMethod = ‘sum’ OR AggMethod='probor'
o DefuzzMethod: Defuzzification method: a string value. It depends on Fuzzy type.
Mamdani type: 'centroid', 'bisector', 'mom', 'som', or 'lom'.
o Sugeno type: 'wtaver', or 'wtsum'.
Syntax: ImpMethod = ‘defuzzification_type_name’
•Inputs
This section needs to start with section indicator, [Input#], at the beginning of the section, where # represents the number of input. There can be multiple inputs and each input definition needs to start with [Input#] (Please refer to the example listed at the end).
o Name: Name of the input. A string value. Write the values between quotation marks (' '). ∙ Syntax: Name= ‘name_of_the_input’
Syntax: Name= ‘name_of_the_input’
o Range of x values: Range of input value. Write the minimum value and maximum value between '[' and ']'
Syntax: Range=[minimum_value maximum_value]
o NumMFs: Number of Input Member functions (MFs)
Syntax : NumMFs= an_integer
o MF #: Member Function properties
Syntax:MF1=‘member_function_name’:‘member_function_type’,[parameter_1 parameter_2 … parameter_n ]
o Member Function Types available (for details refer to the following section)
'dsigmf' : requires 4 parameters.
'gauss2mf' : requires 4 parameters.
'gaussmf' : requires 2 parameters.
'gbellmf' : requires 3 parameters.
'pimf' : requires 4 parameters.
'psigmf' : requires 4 parameters.
'sigmf' : requires 2 parameters.
'smf' : requires 2 parameters.
'trapmf' : requires 4 parameters.
'trimf' : requires 3 parameters.
'zmf' : 2 parameters.
o Member Function parameters
Each member function requires some parameters to completely define the member function. The number of parameters is 4 or less.
•Outputs
This section needs to start with section indicator, [Output#], at the beginning of the section, where # represents the number of input. There can be multiple inputs and each input definition needs to start with [Output #] (Please refer to the example listed at the end).
o Name: Name of the input. a string value. Write the values between quotation marks (' ').
Syntax: Name= ‘name_of_the_input’
o Range: Range of output value. Write the minimum value and maximum value between '[' and ']'
Syntax: Range=[minimum_value maximum_value]
o NumMFs: Number of Input Member functions (MFs)
Syntax: NumMFs= an_integer
o MF #: Member Function properties
Syntax: MF1=‘member_function_name’:‘member_function_type’, [parameter_1 parameter_2 … parameter_n ]
o Member Function Types available for ‘Mamadani’
'dsigmf': requires 4 parameters.
'gauss2mf': requires 4 parameters.
'gaussmf': requires 2 parameters.
'gbellmf': requires 3 parameters.
'pimf': requires 4 parameters.
'psigmf': requires 4 parameters.
'sigmf': requires 2 parameters.
'smf': requires 2 parameters.
'trapmf': requires 4 parameters.
'trimf': requires 3 parameters.
'zmf': nrequires 2 parameters.
o Member Function Types available for ‘Sugeno’
'linear': requires 2 (‘number of inputs’ + 1) parameters
'constant’: requires (‘number of inputs’ + 1) parameters
•Rules
This section needs to start with section indicator, [Rules], at the beginning of the section. The IF-THEN rules defined in this section are used to formulate the conditional statements that are required by fuzzy logic. There can be multiple IF-THEN rules. Each rule consists of four parts: Inputs, Outputs, Rule Weighting, and Operation type. Each rule should start in a new line.
o Syntax: MF#_of_Input1 MF#_of_Input2 … MF#_of_Input#, MF#_of_Output1 …
o MF#_of_Input: indicates the index number of the input member function to be used in the rule.
An integer. Any negative value means 'NOT' operation. (Mathematical definition of 'Not' operation is 1 minus by a variable.)
o MF#_of_Output: indicates the index number of the output member function to be used in the rule. An integer. Any negative value means 'NOT' operation. (Mathematical definition of 'Not' operation is 1 minus by a variable.)
o Rule_Weighting: Rule weighting value. A real number between 0 and 1 (including 0 and 1).
Operation Type: Logic operation type. 1 means 'AND' operation in that rule. 2 means 'OR' operation.
o Example
[Rules]
1 -3, 2 (1): 2
This rule means 'IF MF1 of Input1 OR Not MF3 of Input2, THEN MF2 of Output1, weight is 1'
•FIS Example
For an example 'tipper.fis' file in MATLAB® Fuzzy demo is listed below.
01: % $Revision: 1.1 $
02: [System]
03: Name='tipper'
04: Type='mamdani'
05: NumInputs=2
06: NumOutputs=1
07: NumRules=3
08: AndMethod='min'
09: OrMethod='max'
10: ImpMethod='min'
11: AggMethod='max'
12: DefuzzMethod='centroid'
13:
14: [Input1]
15: Name='service'
16: Range=[0 10]
17: NumMFs=3
18: MF1='poor':'gaussmf',[1.5 0]
19: MF2='good':'gaussmf',[1.5 5]
20: MF3='excellent':'gaussmf',[1.5 10]
21:
22: [Input2]
23: Name='food'
24: Range=[0 10]
25: NumMFs=2
26: MF1='rancid':'trapmf',[0 0 1 3]
27: MF2='delicious':'trapmf',[7 9 10 10]
28:
29: [Output1]
30: Name='tip'
31: Range=[0 30]
32: NumMFs=3
33: MF1='cheap':'trimf',[0 5 10]
34: MF2='average':'trimf',[10 15 20]
35: MF3='generous':'trimf',[20 25 30]
36:
37: [Rules]
38: 1 1, 1 (1) : 2
39: 2 0, 2 (1) : 1
40: 3 2, 3 (1) : 2