Such optimization-based feedback control techniques can deliver significant energy savings while optimizing light quality and occupant comfort. However, a key challenge in the design of the control algorithm lies in the construction of the cost function itself. For example, it is unclear how the choice of the weights ˛Uc,Ub and ˛E affect the overall esthetics of the room or the color quality degradation. Furthermore, although the quality metric Q is meant to evaluate the light field as a whole, in implementation this light field is inferred only through discrete intensity measurements from color sensors at specific locations. As a result, the control system’s performance is heavily tied to the locations of these sensors and blind to the actual light fields generated. For both these reasons, it is critical to develop simulation tools that enable
• assessment of a designed cost function and thus iterative choice of the relative weights of various terms in the cost function, and
• evaluation of sensor measurements and desired setpoints and their correlation to generated light fields.