A Smart Lighting System for Visual Comfort and Energy Savings in Industrial and Domestic Use

Abstract

The goal of this work is to develop a smart light-emitting diode lighting system for industrial and domestic use with several advantages over conventional systems, namely energy saving, high reliability, and visual comfort of interior lighting. This is achieved by integrating a smart control module and a fault diagnosis and prognosis module within a conventional lighting system. The first module controls the lighting level in an energy-efficient way, keeping a desired light level where it is needed while regulating it to a minimum where not required; this is achieved by fully exploiting fuzzy logic and proportional-integrative-derivative controllers. The second module performs fault diagnosis on the light-emitting diode system and predicts when light-emitting diode maintenance should be performed; this is achieved by employing both hardware redundancy and signal-based approaches. Interaction between the two modules permits maintenance of a desired level of light even in the case of failures on one or more light-emitting diodes. The overall system has been experimentally validated in three different scenarios.

Keywords:

• fault diagnosis
• fault-tolerant control
• lighting systems
• home and building automation
• energy efficiency

Additional information

Notes on contributors

Gionata Cimini

Gionata Cimini was born in San Severino Marche (MC), Italy, in 1988. He received his B.Sc. and M.Sc. (summa cum laude) in computing and automation engineering from the Università Politecnica delle Marche, Ancona, Italy, in 2010 and 2012, respectively. Since 2013, he has been a research assistant from the Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Italy. Since November 2013, he has been a Ph.D. student at the same department and a guest scholar at Institutions Markets Technologies (IMT) Lucca Institute for Advanced Studies, Lucca, Italy. His main research interests include advanced control methods, model predictive control, and embedded optimization, with applications in power electronics and motion control.

Alessandro Freddi

Alessandro Freddi received the M.S. in electronic engineering and his Ph.D. in automation, information, and management engineering from Università Politecnica delle Marche (formerly Università di Ancona), Ancona, Italy, in 2008 and 2012, respectively. He worked from 2012 to 2014 as a postdoctoral research fellow at the Department of Information Engineering of Università Politecnica delle Marche, Ancona, Italy. Since 2014, he has been a researcher at Università degli Studi eCampus, Como, Italy. His main research activities are model-based fault diagnosis and fault-tolerant control systems, with applications to unmanned vehicles and assistive robotics.

Gianluca Ippoliti

Gianluca Ippoliti received his master’s degree (summa cum laude) in electronic engineering and his Ph.D. in intelligent artificial systems from Università Politecnica delle Marche (formerly University of Ancona), Ancona, Italy, in 1996 and 2002, respectively. From 1997 to 1998, he was with Institute of Health and Medical Research (INSERM) Unitè 103, Montpellier, France, and then with University of Montpellier I, Montpellier, France, in the framework of the European research projects Human Capital and Mobility (CAMAPN) and Mobile Robotics Technology for Health Care Services Research Network (MOBINET). From 2002 to 2005, he held a postdoctoral position at the Dipartimento di Ingegneria Informatica, Gestionale e dell’Automazione, Università Politecnica delle Marche. Since March 2005, he has been an assistant professor at Università Politecnica delle Marche. He has published more than 130 papers in international journals, books, and refereed conferences. His main research interests include switched systems and supervisory control; neural network based system identification and control; modeling identification and control of robotic, electrical, and electromechanical systems; and mobile robot control and localization.

Andrea Monteriù

Andrea Monteriù received his laurea degree (joint B.Sc./M.Sc. equivalent, summa cum laude) in electronic engineering and his Ph.D. in artificial intelligence systems from Università Politecnica delle Marche, Ancona, Italy, in 2003 and 2006, respectively. His M.Sc. thesis has been developed to the Automation Department of the Technical University of Denmark, Lyngby, Denmark. In 2005, he was a visiting researcher at the Center for Robot Assisted Search & Rescue of the University of South Florida, Tampa, FL. Since 2007, he has been a postdoc and research fellow at the Dipartimento di Ingegneria dell’Informazione of the Università Politecnica delle Marche, where he currently is a contract professor. His research interests include fault diagnosis, fault handling, fault tolerant control, system and control theory, non-linear dynamics and control, periodic systems, stochastic systems, guidance and control of autonomous systems, and applications in a variety of fields, including aerospace, marine, and robotic systems.

Matteo Pirro

Matteo Pirro was born in Loreto (AN), Italy, in 1986 and lives in Porto Recanati (MC). He received his master’s degree (summa cum laude) in electronic engineering from Università Politecnica delle Marche, Ancona, Italy, in 2010. Since 2011, he has been a Ph.D. student in informatics, managerial, and automatics engineering at Dipartimento di Elettronica ed Automatica, Università Politecnica delle Marche. He is currently a visiting scholar at L2S Department at Supelec, France, with Prof. Romeo Ortega as his tutor. He has published about 20 papers in international journals and refereed conferences. His main research interests include linear and non-linear control of electrical and electromechanical systems, power electronics, and renewable energies.