Introduction to Fuzzy Logic in Networks
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Fuzzy logic examples in network applications.
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Introduction to Fuzzy Logic in Networks
- 1. Fuzzy Logic and Adaptive Sampling Edwin Hernandez HCS - Lab
- 3. Membership functions Triangular T() and trapezoidal Trap() All parameters are represented as T(), Trap() or Impulse()
- 4. FLC membership functions deltaV (NC)=T(NC:0, D1, 0) deltaV (CS)=T(CS:D1, D2,D3) deltaV (CL)=T(CL:D2, D3, D4) deltaV (CM)=T(CM:D3, D4, D5) deltaV (CH)=T(CH:D4, D5, D6) NC: No change CS: Change-Slightly CL: Change-Low CM: Change-Medium CH: Change-High DeltaV (Change of Value)
- 5. Membership functions deltaT (Low)=Trap(Low:1, T1, T2) deltaT (med-low)=T(med-low:T1, T2,T3) deltaT (medium)=T(medium:T2, T3, T4) deltaT (med-high)=T(med-high:T3, T4, T5) deltaT (high)=Trap(high:T4, T5, Tmax) deltaT Timming
- 6. Membership Functions output (DH)=Trap(Low:-O1, -O2, -O3) output (DM)=T(DM:-O2, O3,0) output (NC)=T(NC:-O3, 0, O4) output (IM)=T(IM:0, O3, O4) output (IH)=Trap(IH:O4, O5, O6) Output Inc/dec timmers DH: decrease high DM: decrease medium NC: No change IM: Increase more IH: Increase High
- 11. MAX-MIN method
- 12. MAX-DOT Pseudo-code float Output[]; Value[] = GetMembership(inputV, DeltaV[]); // returns a value for Value_chLow, Value_nochange, etc Timming[] = GetMembership(inputT, DeltaT[]); // returns a value for Timming_low, Timming_High, etc For each rule if rule[I] applies then // depending on the Rule Timming/Value applies // and are used in the array Output[] = MAX(Value[I]*Timming[I], Output[]); end; return Defuzzify(Output[])
- 13. Other Applications ATM Admission control and congestion control
- 15. FLC : Rules and Membership functions
- 16. FLC: Rules for the Fuzzy Congestion Controller
- 17. FLC: Defuzzification Rules 1, 2, 4,5,6 apply for IM Tsukamoto’s defuzzification method