1092 IEEE SENSORS JOURNAL, VOL. 13, NO. 3, MARCH 2013 Distributed Illumination Control With Local Sensing and Actuation in Networked Lighting Systems David Caicedo and Ashish Pandharipande, Senior Member, IEEE Abstract— We consider the problem of illumination control in a networked lighting system wherein luminaires have local sensing and actuation capabilities. Each luminaire: 1) consists of a light- emitting diode (LED) based light source dimmable by a local controller; 2) is actuated based on sensing information from a presence sensor, that determines occupant presence, and a light sensor, that measures illuminance, within their respective fields of view; and 3) a communication module to exchange control information within a local neighborhood. We consider distributed illumination control in such an intelligent lighting system to achieve presence-adaptive and daylight-integrated spatial illumi- nation rendering. The rendering is specified as target values at the light sensors, and under these constraints, a local controller has to determine the optimum dimming levels of its associated LED luminaire so that the power consumed in rendering is minimized. The formulated optimization problem is a distributed linear programming problem with constraints on exchanging control information within a neighborhood. A distributed optimization algorithm is presented to solve this problem and its stability and convergence are studied. Sufficient conditions, in terms of parameter selection, under which the algorithm can achieve a feasible solution are provided. The performance of the algorithm is evaluated in an indoor office setting in terms of achieved illuminance rendering and power savings. Index Terms— Daylight and occupancy adaptive lighting, distributed lighting systems, distributed sensing and light actuation, lighting control. I. I NTRODUCTION A DVANCES in semiconductors have brought in a new generation of light sources in the form of light emitting diodes (LEDs). Minitiarization and rapid cost-downs from semiconductorization has also made it possible for greater inte- gration of sensing, communication, computation and control functions into luminaires. This has made intelligent LED lumi- naires feasible, that (i) are dimmable by an associated local controller, (ii) can be actuated based on local sensing inputs such as presence detection and light intensity measurement within the sensor field of view, and (iii) can exchange control information within a local neighborhood using a communica- tion module. We address the problem of illumination control in a system of such intelligent luminaires to achieve energy- efficient illumination rendering over the workspace. Manuscript received September 28, 2012; revised November 10, 2012; accepted November 10, 2012. Date of publication November 21, 2012; date of current version February 4, 2013. The associate editor coordinating the review of this paper and approving it for publication was Prof. Aime Lay-Ekuakille. The authors are with Philips Research, Eindhoven 5656AE, The Netherlands (e-mail: david.caicedo@philips.com; ashish.p@philips.com). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JSEN.2012.2228850 We consider illumination control for indoor office general lighting applications. Office lighting is one of the major constituents of electrical energy consumption in buildings [1]. As such, energy-efficient strategies for illumination rendering in lighting systems are of interest. We consider presence- adaptive, daylight-integrated illumination rendering in this paper. In particular, we want to achieve uniform illumination at an average illuminance of L o WP in an occupied zone and a lower average illuminance of L u WP otherwise over the workspace plane. Local occupancy in a zone is determined by a presence sensor. In office lighting, the illumination distribu- tion achieved at the workspace plane, typically corresponding to desk level, is of most interest. This is a horizontal plane at a certain vertical height from the ceiling plane, in which the luminaires are located. Illuminance is however measured in practice using light sensors placed in the ceiling. As such, light measurement is in a plane different from the one where the spatial illumination rendering is desired. Also, a light sensor measures a spatial average of the light distribution in its field of view. A light sensor calibration step is thus employed to obtain target sensor values. These target light sensor illuminance values then specify the rendering constraints to be satisfied under distributed control. The specifics of the lighting system are described in Section II. For a given realization of occupancy and daylight dis- tribution in the office space, the local controller needs to determine the dimming level of its associated luminaire using local presence and light sensor measurements and commu- nication with controllers in its neighborhood. This problem is mathematically a distributed linear programming problem with constraints on information exchange, and is formulated in Section III. We present a distributed optimization algorithm to obtain a suboptimum solution to this problem, and is described in Section IV. A bound is further obtained on the deviation of the resulting power consumption from that obtained under optimum dimming. In Section V, we analyze stability and convergence of the proposed algorithm. Sufficient conditions are provided for specifying the neighborhood for exchanging control information such that the algorithm can achieve the target sensor values, i.e. a feasible solution is obtained. We evaluate the performance of the distributed illumination control algorithm with an example open office lighting sim- ulation. The performance is evaluated based on the achieved illumination rendering and power savings. A comparison is made with an optimum centralized control algorithm. These numerical results are presented in Section VI. Different lighting control approaches exist in literature [2]–[12], depending on the system architecture, connectivity 1530–437X/$31.00 © 2012 IEEE