Modeling and feedback control of color-tunable LED lighting systems

This paper presents a color-science-based approach to feedback control design of color-tunable LED lighting systems for smart spaces. The general design problem is posed as the minimization of a cost function consisting of metrics that capture light quality, energy consumption and human comfort. A linear light transport map is used for modeling and identifying the optical fingerprint of the room. The feedback control law is then derived based on the identified model through gradient-based optimization of the cost function. Finally, experimental results are presented to highlight the performance of the feedback control law in terms of (1) energy savings, (2) delivered light quality, (3) adaptivity to external disturbances (such as daylighting) and (4) human comfort.