What is Fuzzy Logic?
Fuzzy Logic is a form of logic that, in contrast to classical “true/false” logic (0 or 1), works with degrees of truth — values between 0 and 1. It is used in systems where human reasoning, vague concepts and uncertain inputs play a role.
Fuzzy Logic = “smart logic” for situations that are not black and white.
🎯 How does Fuzzy Logic work?
| Standard logic | Fuzzy logic |
|---|---|
| On or off (0 or 1) | Greyscale values between 0 and 1 |
| Temp > 50 = WARM | Temp = “a bit warm”, “very warm”, “lukewarm” (graded) |
| Decisions via IF-THEN | Decisions via IF fuzzy rules, weighted |
A Fuzzy Controller translates “vague” language such as “almost full” or “rising rapidly” into concrete actions through a set of fuzzy rules.
🧠 Structure of a Fuzzy Logic system
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Fuzzification Raw input (e.g. temperature = 63°C) is translated into a “degree of membership” in a fuzzy set, e.g. “warm” = 0.7, “hot” = 0.3
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Rule evaluation IF temperature is “warm” AND rate of rise is “fast” THEN fan = “high”
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Defuzzification The fuzzy result (e.g. “high” = 0.8, “medium” = 0.2) is converted into a concrete output signal, for example 78% valve opening
🏭 Fuzzy Logic in practice
| Application | Fuzzy behaviour |
|---|---|
| HVAC control | Adjust ventilation based on perceived comfort rather than threshold values |
| Silo level control | Drive a pump based on the speed and trend of the level |
| Robot control | Adjust gripping force depending on material softness |
| Process control | Fuzzy PID tuning under variable conditions |
🔗 Fuzzy Logic vs. PID
| Aspect | Fuzzy Logic | PID |
|---|---|---|
| Input type | Vague, semantic input (“fairly fast”, “almost full”) | Numeric (PV, SP, error value) |
| Flexibility | Highly adaptive, tolerant of uncertainty | Effective for stable, linear systems |
| Knowledge-based | Rules based on expert knowledge | Based on mathematical tuning |
📌 In summary
Fuzzy Logic is a smart way to control systems that are not exactly predictable or linear — ideal for “human-like” decision-making in automation.