Energy harvesting in smart industrial machines: Generating the energy you need from the sources you know
A smart system can be defined as a system incorporating sensing, actuation, control and communication, in order to adjust to or inform about the system’s context or own condition. Through technological advances, particularly in microelectronics, “smartness” has been demonstrated in a number of application domains, ranging from smart healthcare and smart homes, to smart cities and smart industries. To realize smartness on large scale, however, the energy supply to the necessary technologies is still a challenge. Batteries have been the go-to solution in cases where a fixed electrical infrastructure is infeasible or impossible. Batteries, however, have a limited energy capacity and lifetime, resulting in maintenance requirements that are typically undesirable at scale. Consequently, the conversion of ambient energy sources – commonly referred to as energy harvesting – is investigated as an alternative.
In this talk, an introduction as to what energy harvesting is, what it can be used for, and what challenges it faces, will be given. It will provide a holistic view, covering examples of energy sources to be exploited, conversion mechanisms to be utilized, and implementation aspects to be considered for system integration. During the talk, concrete cases of energy harvesting systems for smart industry applications will be explored in order to provide tangible examples. Moreover, open research challenges for energy harvesting and self-powered smart systems will be addressed, and an outlook on research trends given.
Hybrid Dynamical systems : a time scale approach
Immunity to change: Artificial Immune Systems (AIS) for Cyber-Physical Systems (CPS)
In cyber-physical systems (CPS), such as intelligent production and service systems (e.g. flexible/reconfigurable manufacturing systems), and intelligent transportation systems (public transportation and traffic control), change can have important impacts on organization, performance, quality of service and user safety and satisfaction. Change can be expected or unexpected. It can be related to product/service requirements and design, resource availability and reliability, process capability, and environment (natural, social, legal, economic) stability. For example, change in production systems may appear in the form of several kinds of disturbances (also called disruptions), such as supply unavailability, machine failures, tool breakage, workforce absenteeism, quality problems, rush orders, etc. In transportation systems, accidents, traffic congestion, or freeing the way to emergency vehicles (ambulances, firefighters, etc.) may disturb the fluidity of traffic and affect the expected execution of preset organization and pre-established timetables of public transportation resources (buses, trains, metros, trams, etc.). Thus, detecting disturbances on-line, and identifying their risky consequences timely are important tasks that enable advised decision-making and reaction to maintain performance and quality of service. The speech will provide an overview of artificial immune systems (AIS) as an artificial intelligence paradigm to achieve distributed and adaptive control of change and disturbances in CPS. A generic reactive decision-making framework will be presented, on-going developments in manufacturing and transportation systems will be described, and future research opportunities will be highlighted.