Abstract:
Building designers aim to create buildings with high quality internal environments
which are energy and cost efficient in their use. Failure to attain these objectives
simultaneously can lead to reduced building occupant productivities. An important
aspect of the building services system which can have a major effect on the provision of
occupant comfort within a building is the adopted control strategy.
The research project investigated the use of fuzzy control strategies as a means of
achieving good standards of comfort provision for occupants while maintaining or
improving energy and cost efficiencies for the operation of the building HVAC services.
This represented a multi-variant controls objective which was capable of being fulfilled
by a fuzzy controller.
A one zone building computer model was developed using Matlab and Simulink
software as a platform for the development of fuzzy control strategies. The model
incorporated building services Heating Ventilating and Air-Conditioning (HVAC)
system models. A Proportional + Integral + Derivative (PID) control strategy was used
as a benchmark control methodology against which to compare the developed fuzzy
control strategies.
Three types of fuzzy controller were developed during the course of the research project.
These were a Proportional Derivative Fuzzy Controller (PDFC), a Fuzzy Ventilation
Controller, and the Fuzzy High Level Controller. The PDFC used the inputs of error and
rate of change of error from a specified zone environmental condition set point in much
the same way as a PID controller would to control the HVAC plant. Simulation results
indicated that the PDFC control strategy was capable of achieving performance levels
equal to the conventional PID control strategy. The Fuzzy Ventilation Controller was
used to control the rate of fresh outside air entering the building zone through the
mechanical ventilation system in order to make use of the "free" cooling and
dehumidification available by purging the indoor air when possible. Simulation results
showed improvements in the indoor environmental quality provided, and the energy
efficiency and cost efficiency of running the HVAC plant. Finally, the Fuzzy High Level
Controller used a fuzzy supervisor to control the actions of the fuzzy ventilation
controllers. Simulation results showed that the fuzzy supervisor was able to improve the
comfort conditions provided and the energy and cost efficiencies of the operation of the
HVAC plant when compared to the use of the fuzzy ventilation control strategies alone.
