CPS: Small: Delays, Clocks, Timing and Reliability in Networked Control Systems: Theories, Protocols and Implementation
Lead PI:
Panganamala Kumar
Abstract
The objective of this research is to address issues related to the platform revolution leading to a third generation of networked control systems. The approach is to address four fundamental issues: (i) How to provide delay guarantees over communication networks to support networked control? (ii) How to synchronize clocks over networks so as to enable consistent and timely control actions? (iii) What is an appropriate architecture to support mechanisms for reliable yet flexible control system design? (iv) How to provide cross-domains proofs of proper performance in both cyber and physical domains? Intellectual Merit: Currently neither theory nor networking protocols provide solutions for communication with delay constraints. Coordination by time is fundamental to the next generation of event-cum-time-driven systems that cyber-physical systems constitute. Managing delays and timing in architecture is fundamental for cyberphysical systems. Broader Impact: Process, aerospace, and automotive industries rely critically on feedback control loops. Any platform revolution will have major consequences. Enabling control over networks will give rise to new large scale applications, e.g., the grand challenge of developing zero-fatality highway systems, by networking cars traveling on a highway. This research will train graduate students on this new technology of networked control. The Convergence Lab (i) has employed minority undergraduate students, including a Ron McNair Scholar, as well as other undergraduate and high school researchers, (ii) hosts hundreds of high/middle/elementary school students annually in Engineering Open House. The research results will be presented at conferences and published in open literature.
Panganamala Kumar
Performance Period: 09/01/2011 - 08/31/2013
Institution: Texas A&M Engineering Experiment Station
Sponsor: National Science Foundation
Award Number: 1232602