Tue06Jun2017Tue25Jul2017Robert Bosch Centre for Cyber-Physical Systems, Hands-on LabShow details
Instructor: Darshak Vasavada
Every Tuesday in June (6, 13, 20, 27) and July (4, 11, 18, 25)
Lectures from 5.00-7.00 pm and Lab from 7.00-7.30 pm
Students are expected to work on the problems and platforms at home
The course is aimed for students from various fields, who do not have prior experience in electronics or programming but are interested in developing embedded systems specific to their field of technology. This course will enable students from various Science and Engineering branches to build simple embedded systems, or effectively team up with Electronics and Computer Science engineers to build embedded systems with higher complexity.
The following topics will be discussed:
- Microprocessor basics
- Introduction to programming
- Structure of a stand-alone system
- Programming I/O devices
- Communication between devices
- Communication with the external world
- Students presentations
None. However, exposure to some programming language will be useful. If not, the student may have to put in a extra effort to learn simple programming.
Thank you for your interest in the course. Unfortunately, it is fully booked.
Tue25Jul201715.00-16.00Robert Bosch Centre for Cyber-Physical Systems, Seminar HallShow details
As we move away from fossil fuels toward renewable energy sources such as solar and wind, inexpensive energy storage technologies are required. This is so since renewable energy sources, such as solar and wind, are intermittent. An alternative to batteries – which are quite expensive – is “smart loads”, such as air conditioners equipped with computation and communication capability. With appropriate software, the power consumption of air conditioning -- and many other loads -- can be varied around a baseline. This variation is analogous to the charging and discharging of a battery. Loads equipped with such intelligence have the potential to provide a vast and inexpensive source of energy storage. Two principal challenges in creating a reliable virtual battery from millions of consumer loads include (1) maintaining consumers’ Quality of Service (QoS) within strict bounds, and (2) coordinating the actions of loads with minimal communication to ensure accurate reference tracking by the aggregate.
When the loads in question are residential loads that can either turned on or off, the coordination problem suffers from a combinatorial explosion. This talk describes our work in addressing this challenge by using randomized control, in which control actions are decided probabilistically. A key advantage of this approach is that aggregate behavior of a collection of loads can be approximated by an LTI (linear time invariant) system. Two classes of on/off loads will be considered: deferrable loads, such as water pumps, and thermostatically controlled loads (TCLs) such as air conditioners. The latter is more challenging since the additional randomness introduced by weather and consumer behavior. While the former can be modeled by a finite-space space Markov chain, the latter requires an infinite state space.
About the Speaker
Prabir Barooah is an Associate Professor of Mechanical and Aerospace Engineering at the University of Florida, where he has been since 2007. He received the Ph.D. degree in Electrical and Computer Engineering in 2007 from the University of California, Santa Barbara. From 1999 to 2002 he was a research engineer at United Technologies Research Center, East Hartford, CT. He received the M.S. degree in Mechanical Engineering from the University of Delaware in 1999 and the B.Tech. degree in Mechanical Engineering from the Indian Institute of Technology Kanpur, in 1996.
Dr. Barooah is the winner of Endeavour Executive Fellowship (2016) from the Australian Government, ASEE-SE (American Society of Engineering Education, South East Section) outstanding researcher award (2012), NSF CAREER award (2010), General Chairs' Recognition Award for Interactive papers at the 48th IEEE Conference on Decision and Control (2009), best paper award at the 2nd International Conference on Intelligent Sensing and Information Processing (2005), and NASA group achievement award (2003).