Create a Mamdani Fuzzy Decision System - Engineering Assignment Help

Assignment Task :

This coursework is worth 20% of the year's assessment. You should submit a zipped file via the Moodie site consisting of:

• report with solutions to the exercise below in .doc or .pdf format (maximum 3 pages) and

• all .fis files generated to solve the exercise with meaningful file names such as Q2.fis, Q4a.fis etc). 

Exercise Create a Mamdani fuzzy decision system described by three inputs X1, X2 and X3, one output Y and up-to 27 meaningful rules. The system should model a decision tool inspired from your course topics, e.g. risk assessment based on credit history, age and salary level; security assessment based on level of protection, surveillance and hour of access etc. If no other idea sounds applicable, you may use the default example of a decision system for one of these examples. You may use either Octave Fuzzy Logic Toolbox or any Fuzzy Logic Toolbox. The inputs and outputs are defined by up-to 4 (and minimum 2, at your choice) appropriate membership functions, each to represent the linguistic terms. The rule base may look similarly to: IF X1 is small AND X2 is large THEN Y = small negative IF X1 is large OR X2 is large THEN Y = large positive IF X1 is small OR X2 is small THEN Y = small negative IF X1 is large AND X2 is small THEN Y = small positive 
 

Questions

1 Describe the system chosen in free text. Clarify the inputs and output domains.

2 Define the input and output variables providing for each linguistic variable the fuzzy values and the graphical representation of their membership functions. Motivate their interval(s). Choose AND function as the min operator; aggregation and OR as the max operator, and Gaussian/sigmoidal membership functions. You are expected also to submit the fuzzy inference system (FIS) file of the system you designed.

3 Present an inference for output Y graphically, where X 1 , X2 and X3 have given values of your choice ("graphically" means using Rule Viewer and setting the values in it). Interpret the results.

4 Draw the output surface and briefly describe and discuss changes relative to the original system output surface for the case when Trapezoidal membership function (trapmJ) is used as membership function for all system variables.

5 Investigate the different defuzzification techniques available in Octave Fuzzy Logic Toolbox and carry out an analysis of their effects on the output.

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