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.