Smart indoor lighting systems with luminaire-based sensing: A review of lighting control approaches

Pandharipande, Ashish; Caicedo, David

doi:10.1016/j.enbuild.2015.07.035

Cited by 153 publications

(68 citation statements)

References 48 publications

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“…Expressions (10) and (12) where used in [1] to calculate the values of the converter components (C P , C R and L R ), but they can also be combined with (7) to (9) to calculate how the LED power P LED and the switching frequency ω are modified as a function of q and κ once the component values are known. Using the design parameters summarized on Table 1, the theoretical representation of i LED , P LED and i res(peak) as a function of the operating frequency where obtained.…”

Section: Of 22mentioning

confidence: 99%

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Closed Loop Control of a Series Class-E Voltage-Clamped Resonant Converter for LED Supply with Dimming Capability

et al. 2019

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In this work, a new closed-loop control system is applied to a class-E resonant DC-DC converter with voltage clamp used for light-emitting diode (LED) supply. The proposed power topology was first described by Ribas et al. in a recent work. In the present paper, the LED current is sensed and used to implement a feedback control loop instead of the simplified feedforward scheme used in this previous reference. To design the control, a novel, simplified small-signal model is presented. This model is used to analyze the converter behavior as a function of the output power. The proposed approximation is significantly simpler than the multifrequency averaging technique normally used to analyze resonant converters. The feedback control loop is designed to reduce the LED low frequency current ripple while providing dimming control. Both the model and the control are verified by simulation and laboratory experimentation and the results obtained are in good accordance with the expected values.

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Section: Of 22mentioning

confidence: 99%

“…Embedded software on microcontrollers further enables adding a first layer of intelligence to LED lighting systems. In these lighting systems, complex control strategies can be used to maximize user comfort while minimizing power consumption [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Closed Loop Control of a Series Class-E Voltage-Clamped Resonant Converter for LED Supply with Dimming Capability

et al. 2019

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“…[7][8][9] In lighting control systems, light sensors are typically located at the ceiling to measure the illumination at the workplace. 5 This configuration benefits from simplified placement, installation and wiring of sensors to the luminaire's power connection. On the other hand, since the sensors are located at the ceiling, sensor measurements do not correspond to the illumination at the workplace.…”

Section: Introductionmentioning

confidence: 99%

Sensor-driven, human-in-the-loop lighting control

Tan

Caicedo

Pandharipande

et al. 2017

Lighting Research & Technology

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Smart indoor lighting systems use occupancy and light sensor data to adapt artificial lighting in accordance with changing occupancy and daylight conditions. Such systems can be designed to reduce lighting energy consumption significantly. However, these systems cannot account for individual user preferences at the workplace in real time. We propose a sensor-driven, human-in-the-loop lighting system that incorporates user feedback in addition to occupancy and light sensor inputs. In this system, luminaires transmit unique visible light communication identifier signals. By processing the image captured by a smartphone camera, a user obtains two pieces of information: visible light communication identifiers of luminaires in the vicinity and average image pixel value. A control algorithm is designed that incorporates these user inputs along with occupancy and light sensor inputs to determine the dimming levels of the luminaires to achieve illumination levels acceptable to users. We compare the performance of the proposed lighting control system with a sensor-driven lighting control system in an office test bed.

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“…The paper [1] presented a case study of energy management in an intelligent building based on the integration of Wireless Sensor Networks (WSN). In this line, having an efficient management of the lighting control system of buildings is essential for energy optimization and it has already been addressed in the literature [2]. In addition, it has been proved that the use of WSN for low-cost energy optimization of green building lighting systems is a viable option to consider [3].…”

Section: Introductionmentioning

confidence: 99%

Automatic Supervision of Temperature, Humidity, and Luminance with an Assistant Personal Robot

et al. 2017

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Smart environments and Ambient Intelligence (AmI) technologies are defining the future society where energy optimization and intelligent management are essential for a sustainable advance. Mobile robotics is also making an important contribution to this advance with the integration of sensors and intelligent processing algorithms. This paper presents the application of an Assistant Personal Robot (APR) as an autonomous agent for temperature, humidity, and luminance supervision in human-frequented areas. The robot multiagent capabilities allow gathering sensor information while exploring or performing specific tasks and then verifying human comfortability levels. The proposed methodology creates information maps with the distribution of temperature, humidity, and luminance and interprets such information in terms of comfort and warns about corrective actuations if required.

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Smart indoor lighting systems with luminaire-based sensing: A review of lighting control approaches

Cited by 153 publications

References 48 publications

Closed Loop Control of a Series Class-E Voltage-Clamped Resonant Converter for LED Supply with Dimming Capability

Closed Loop Control of a Series Class-E Voltage-Clamped Resonant Converter for LED Supply with Dimming Capability

Sensor-driven, human-in-the-loop lighting control

Automatic Supervision of Temperature, Humidity, and Luminance with an Assistant Personal Robot

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