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Illumination gain estimation and tracking in a distributed lighting control system

机译:分布式照明控制系统中的照明增益估计和跟踪

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We consider a distributed lighting control system with multiple networked luminaires, each equipped with a light and presence sensor, and a local controller. Using local sensor inputs and information exchange with limited neighboring controllers, each local controller determines the optimum dimming level of its luminaire so that the lighting power consumption is minimized. This is done under net illumination constraints specified in terms of light sensor set-points. The underlying optimization problem requires knowledge of the illumination gains, i.e. the contributions of luminaire light output to the light sensors. Reflectance changes, e.g. due to occupancy changes or object movements in the environment can change the illumination gains over time, thus affecting the achieved illumination. We address the problem of illumination gain estimation and tracking in a lighting system with distributed asynchronous controllers. A Euclidean projection of the best linear unbiased estimator on the non-negative orthant is used as an initial illumination gain estimate and bounds on mean-squared error performance are obtained. A recursive calibration mechanism to track gain changes is proposed. Illumination performance improvements are shown by numerical results using photometric data.
机译:我们考虑一个分布式照明控制系统,该系统具有多个联网的照明器,每个照明器都配备有照明和状态传感器以及本地控制器。使用本地传感器输入并与有限的相邻控制器进行信息交换,每个本地控制器确定其照明设备的最佳调光级别,从而将照明功耗降至最低。这是在根据光传感器设定点指定的净照明约束下完成的。潜在的优化问题需要了解照明增益,即照明光输出到光传感器的贡献。反射率变化,例如由于占用率的变化或环境中物体的移动会随时间改变照明增益,从而影响获得的照明。我们解决了具有分布式异步控制器的照明系统中照明增益估计和跟踪的问题。将最佳线性无偏估计量在非负正割线上的欧几里得投影用作初始照明增益估计,并获得均方误差性能的界限。提出了一种跟踪增益变化的递归校准机制。使用光度数据的数值结果显示了照明性能的提高。

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