16.3 FUZZY LOGIC

---

Ø•Û��ÛØ“Û

Rules are created which make sense to humans, for example when driving a car some acceleration rules may be,

if LOUD_NOISE and FAST_SPEED then SLOW_SPEED

if QUIET_NOISE and FAST_SPEED then SAME_SPEED

Each or the rule conditions, and results, can be represented with a 1 dimension matrix,

LOUD_NOISE = { 0.0 0.1 0.5 1.0 }

QUIET_NOISE = {1.0 0.5 0.1 0.0 }

FAST_SPEED = { 0.0 0.2 0.7 1.0 }

SLOW_SPEED = { 1.0 0.5 0.2 0.0 }

SAME_SPEED = { 1.0 1.0 1.0 1.0 }

The sets are considered normalized from minimum to maximum. For example is the NOISE sets were from 20dB to 100dB, then a noise level of 80dB would result in a value of 0.5, or a 50% memebership. This way you can say if the noise is `absolutely loud', giving a value of 1.0, or `a bit loud' giving a value of .5.

The matrices are combined using the rules to get a result matrix

Because the conditions (like LOUD_NOISE) are defined with a sort of weight, or memebership rules are easier to make up.

Fuzzy logic controllers have been very successful at solving control problems.