State-of-the-Art feedback control of lighting depends on point sensor measurements for light field generation. However, since the occupant’s perception depends on the entire light field in the room instead of the illumination at a limited set of points, the performance of these lighting control systems may be unsatisfactory. Therefore, it is critical to reconstruct the light field in the room from point sensor measurements and use it for feedback control of lights. This paper presents a framework for using graphical rendering tools along with point sensor measurements for the estimation of a light field and using these estimates for feedback control. Computer graphics software is used to efficiently and accurately model building spaces, while a game engine is used to render different lighting conditions for the space on the fly. These real-time renderings are then used together with sensor measurements to estimate and control the light field in the room using an optimization-based feedback control approach. We present a set of estimation algorithms for this purpose and analyze their convergence and performance limitations. Finally, we demonstrate closed loop lighting control systems that use these estimation algorithms and compare their relative performance, highlighting their benefits and disadvantages.
- Dynamic Systems and Control Division
Light Field Estimation and Control Using a Graphical Rendering Engine
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Afshari, S, Jia, L, Radke, RJ, & Mishra, S. "Light Field Estimation and Control Using a Graphical Rendering Engine." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 1: Active Control of Aerospace Structure; Motion Control; Aerospace Control; Assistive Robotic Systems; Bio-Inspired Systems; Biomedical/Bioengineering Applications; Building Energy Systems; Condition Based Monitoring; Control Design for Drilling Automation; Control of Ground Vehicles, Manipulators, Mechatronic Systems; Controls for Manufacturing; Distributed Control; Dynamic Modeling for Vehicle Systems; Dynamics and Control of Mobile and Locomotion Robots; Electrochemical Energy Systems. San Antonio, Texas, USA. October 22–24, 2014. V001T07A004. ASME. https://doi.org/10.1115/DSCC2014-6163
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