Project acronym APOLLO
Project Advanced Signal Processing Technologies for Wireless Powered Communications
Researcher (PI) Ioannis Krikidis
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Summary
Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Max ERC Funding
1 930 625 €
Duration
Start date: 2019-07-01, End date: 2024-06-30
Project acronym FAULT-ADAPTIVE
Project Fault-Adaptive Monitoring and Control of Complex Distributed Dynamical Systems
Researcher (PI) Marios Polycarpou
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary "The emergence of networked embedded systems and sensor/actuator networks has facilitated the development of advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to activate the appropriate actuators and achieve the desired control objectives. However, in situations where a fault arises in some of the components (e.g., sensors, actuators, communication links), or an unexpected event occurs in the environment, this may lead to a serious degradation in performance or, even worse, to an overall system failure. There is a need to develop a systematic framework to enhance the reliability, fault-tolerance and sustainability of complex distributed dynamical systems through the use of fault-adaptive monitoring and control methods. The work proposed here will contribute to the development of such a framework with emphasis on applications related to critical infrastructure systems (e.g., power, water, telecommunications and transportation systems). It will provide an innovative approach based on the use of networked intelligent agent systems, where the state of the infrastructure is monitored and controlled by a network of sensors and actuators with cooperating agents for fault diagnosis and fault tolerant control. A hierarchical fault diagnosis architecture will be developed, with neighbouring fault diagnosis agents cooperating at a local level, while transmitting their information, as needed, to a regional monitoring agent, responsible for integrating in real-time local information into a large-scale “picture” of the health of the infrastructure. A key motivation is to exploit spatial and temporal correlations between measured variables using learning methods, and to develop the tools and design methodologies that will prevent relatively “small” faults or unexpected events from causing significant disruption or complete system failures in complex distributed dynamical systems."
Summary
"The emergence of networked embedded systems and sensor/actuator networks has facilitated the development of advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to activate the appropriate actuators and achieve the desired control objectives. However, in situations where a fault arises in some of the components (e.g., sensors, actuators, communication links), or an unexpected event occurs in the environment, this may lead to a serious degradation in performance or, even worse, to an overall system failure. There is a need to develop a systematic framework to enhance the reliability, fault-tolerance and sustainability of complex distributed dynamical systems through the use of fault-adaptive monitoring and control methods. The work proposed here will contribute to the development of such a framework with emphasis on applications related to critical infrastructure systems (e.g., power, water, telecommunications and transportation systems). It will provide an innovative approach based on the use of networked intelligent agent systems, where the state of the infrastructure is monitored and controlled by a network of sensors and actuators with cooperating agents for fault diagnosis and fault tolerant control. A hierarchical fault diagnosis architecture will be developed, with neighbouring fault diagnosis agents cooperating at a local level, while transmitting their information, as needed, to a regional monitoring agent, responsible for integrating in real-time local information into a large-scale “picture” of the health of the infrastructure. A key motivation is to exploit spatial and temporal correlations between measured variables using learning methods, and to develop the tools and design methodologies that will prevent relatively “small” faults or unexpected events from causing significant disruption or complete system failures in complex distributed dynamical systems."
Max ERC Funding
2 035 200 €
Duration
Start date: 2012-04-01, End date: 2018-03-31
