Personally controlled air movement can maintain or enhance thermal comfort in warm environments and reduce energy consumption. Unlike controlling a personal fan, using a system of fans for multiple occupants is difficult as it is hard to find an appropriate fan speed setting that maximizes occupants’ satisfaction. Since limited work has been carried out on this issue, in this paper, a novel cooperative control approach for a system of fans is proposed to provide optimized air movement for multiple occupants. This is the first time that a system of fans is controlled cooperatively in the research of built environment. The proposed approach predicts airflow in a cost-effective manner by calibrating the fans in the real environment. The operation of the fans is optimized by minimizing the worst-case deviation between the actual air speed and the desired air speed, which can be determined based on either the PMV – SET model or the occupants’ feedback. This minimax-error problem is formulated as an equivalent linear programming problem which can be solved using standard methods. The proposed approach was tested in two different indoor scenarios respectively by 1) measuring air speed directly in a business conference room and 2) involving human subject surveys in a university classroom. In the first experiment, the measured air speeds after optimization are closer to the target values at all tested temperature levels (26 °C, 27.5 °C and 29 °C) indicating improved thermal comfort. In the second experiment, only 62% of the occupants (totally 34) are satisfied with slightly increased room temperature (around 26.5 °C) before optimization, while this number increased to 94% after optimization.