Fuzzy Logic Control of HVAC Systems

Report
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
• Comparing to other research
• Comparing to Two-Position model
Approach
• Error function
– TDesired – TMeasured(t) = Error(t)
• Membership functions for error
– Change fan speed based on error membership
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
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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