Efficient distributed control of light-emitting diode array lighting systems

Dong, Jianfei; Pandharipande, Ashish

doi:10.1364/ol.37.002910

Cited by 12 publications

(8 citation statements)

References 11 publications

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“…The tracking error is e(τ ) = r(τ ) − y(τ ). Substituting the illuminance y(τ ) in (11) into this expression, e(τ ) then takes the following form.…”

Section: A the Illuminance Modelmentioning

confidence: 99%

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Identification and Robust Control of the Nonlinear Photoelectrothermal Dynamics of LED Systems

Dong

Zhang

2017

IEEE Trans. Ind. Electron.

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In lighting systems consisting light emitting diodes (LEDs), excessive temperature is a main cause of degraded luminous efficacy, which leads to reduced average illuminance and distorted illumination rendering. Modeling the thermal dynamics of LEDs is hence essential in designing thermal dissipators and controllers for maintaining constant illuminance or chromaticity. In the existing literature, both physical modeling and system identification have been proposed, which all find the dependence of the temperature on the input power. When the power fluctuates, e.g. due to dimming control, the thermal dynamics becomes nonlinear. Moreover, when a photoelectrothermal (PET) model is used in control synthesis, the nonlinearity due to the product of the temperature dependent efficacy and the input power must be considered. These nonlinearities are either ignored or linearized in most existing methods. The main contribution of this work is treating the aforementioned nonlinearities in a linear parameter varying (LPV) framework. First, the nonlinear thermal dynamics is identified by LPV system identification techniques. Then, a controller to track reference illuminance is designed by H∞ control techniques to be robust to both the temperature and the disturbance from ambient light. The identification data and the designed controller are collected from and verified on real experimental setup.

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“…The tracking error is e(τ ) = r(τ ) − y(τ ). Substituting the illuminance y(τ ) in (11) into this expression, e(τ ) then takes the following form.…”

Section: A the Illuminance Modelmentioning

confidence: 99%

“…In terms of controlling LED lighting systems, one track of research is by feed forward control, e.g. in [9]- [11]. Another track is by feedback control, e.g.…”

Section: Introductionmentioning

confidence: 99%

Identification and Robust Control of the Nonlinear Photoelectrothermal Dynamics of LED Systems

Dong

Zhang

2017

IEEE Trans. Ind. Electron.

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“…Under different system frameworks and assumptions on sensor placement, convex optimization techniques have been studied in [16][17][18][19] for application in distributed lighting control. In [16,17], knowledge of illumination contributions from luminaires at the workspace plane was assumed, while in [18,19], light sensors at workspace plane were considered to measure the illumination contribution. In [6], a distributed interior-point type of method was presented for use in distributed lighting control systems with constraints on communication and with sensors colocated at luminaires.…”

Section: Control Algorithmsmentioning

confidence: 99%

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

Pandharipande

Caicedo

2015

Energy and Buildings

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152

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“…Many recent studies analyzed low energy efficiency and high user comfort within smart LED systems in different scenarios [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. More precisely, refs.…”

Section: Introductionmentioning

confidence: 99%

Smart Dimmable LED Lighting Systems †

Petkovic

Bajović

Vukobratović

et al. 2022

Sensors

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This paper proposes energy-efficient solutions for the smart light-emitting diode (LED) lighting system, which provides minimal energy consumption while simultaneously satisfying illuminance requirements of the users in a typical office space. In addition to artificial light from dimmable LED lamps, natural daylight coming from external sources, such as windows, is considered as a source of illumination in an indoor environment. In order to reduce total energy consumption, the smart LED system has the possibility to dim LED lamps, resulting in reduced LED output power. Additionally, various LED lamps’ functionality, such as semi-angle of the half illuminance and LED tilting, are introduced as an additional parameter to be optimized to achieve greater energy saving of the designed system. In order to properly exploit external lighting, the idea to reduce overall daylight intensity at a users’ location is realized by the option to dim the windows with a shading factor. Based on the users’ requirements for a minimal and desired level of illumination, the proposed optimization problems can be solved by implementing different optimization algorithms. The obtained solutions are able to give instructions to a smart LED system to manage and control system parameters (LEDs dimming levels, semi-angles of the half illuminance, orientation of LEDs, the shading factor) in order to design total illumination, which ensures minimal energy consumption and users’ satisfaction related to illuminance requirements.

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Efficient distributed control of light-emitting diode array lighting systems

Cited by 12 publications

References 11 publications

Identification and Robust Control of the Nonlinear Photoelectrothermal Dynamics of LED Systems

Identification and Robust Control of the Nonlinear Photoelectrothermal Dynamics of LED Systems

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

Smart Dimmable LED Lighting Systems †

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