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Fuzzy Logic Control of HVAC Systems

Fuzzy Logic Control of HVAC Systems. Drew Brunning. Motivation. Buildings consume ≈ 50% of world’s energy Fuzzy logic control more efficient Still being researched. Types of HVAC Controls. Two-Position Control (Most Common) Floating Control PID ANN Fuzzy Logic. Comparison.

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Fuzzy Logic Control of HVAC Systems

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  1. Fuzzy Logic Control of HVAC Systems Drew Brunning

  2. Motivation • Buildings consume ≈ 50% of world’s energy • Fuzzy logic control more efficient • Still being researched

  3. Types of HVAC Controls • Two-Position Control (Most Common) • Floating Control • PID • ANN • Fuzzy Logic

  4. Comparison • Comparing to other research • Comparing to Two-Position model

  5. Approach • Error function • TDesired – TMeasured(t) = Error(t) • Membership functions for error • Change fan speed based on error membership

  6. Simplistic Building Model • Model as rectangular prism • Makes modest assumptions about air pressure/density • Interacts via conduction and convection • Constants averaged among brick, glass, and wood • Not terribly important to the controller

  7. Expected Results • Less energy consumption • Dependent on model and assumptions • Less fluctuation about Tdesired • Same or better time to temperature range

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