This project is to develop dynamical models of distributed computation systems that are resilient to noise, unreliable communication and other source uncertainty. The key idea is centered on the development of optimization systems. These are dynamical systems that (solve) stabilize around the optimal solution of a (static) convex optimization problem. If the optimization problem is separable, then the designed dynamic system decomposes into a set of locally interacting dynamic systems.

The objective of this project has been to apply the techniques developed for communications networks to collaborative, intelligent vehicles. The techniques are applied to a lane merge protocol that assists a driver who is merging between two vehicles in an adjacent lane. The previous work that has been reported on this project includes: a multiple stack, layered architecture; a strategy for using synchronized clocks; and the probabilistic verification of protocols. 

AquaSCALE is a cyber-physical-human middleware for gathering, analyzing and adapting operations of increasingly failure-prone community water services. Today, detection of anomalous events in civil infrastructures (e.g. water pipe breaks and leaks) is time consuming and often takes hours or days. AquaSCALE leverages dynamic data from multiple information sources including IoT sensing data, geophysical data, human input, and simulation and modeling engines to accurately and quickly identify vulnerable spots in water networks.

How much should a person be allowed to interact with a controlled machine? If that machine is easily destabilized, and if the controller operating it is essential to its operation, the answer may be that the person should not be allowed any control authority at all. Using a combination of techniques coming from machine learning, optimal control, and formal verification, the proposed work focuses on a computable notion of trust that allows the embedded system to assess the safety of instruction.

This project is developing a formal methods approach to meet temporal logic specifications in traffic control. Formal methods offer efficient techniques for proving the correct operation of systems, such as computer programs and digital circuits, and for designing systems that are correct by construction. This project is bringing these powerful techniques to bear on traffic networks.

We investigate the ability of a collection of deferrable energy loads to behave as a battery; that is, to absorb and release energy in a controllable fashion up to fixed and predetermined  limits on volume, charge rate and discharge rate. We derive bounds on the battery capacity that can be realized and show  that there are fundamental trade-offs between battery parameters.

Having a shared and accurate sense of time is critical to distributed Cyber-Physical Systems (CPS) and the Internet of Things (IoT). Thanks to decades of research in clock technologies and synchronization protocols, it is now possible to measure and synchronize time across distributed systems with unprecedented accuracy. However, applications have not benefited to the same extent due to limitations of the system services that help manage time, and hardware-OS and

The smart grid is a large-scale, societal-level hybrid cyber-physical system with tight coupling between cyber and physical components.  Ensuring availability and reliability of power requires maintaining stability of the power grid even as increasing demand and uncertain renewable power sources push the power system close to its operation limit.  In addition, the cyber-enabled grid has multiple entry points, leaving it highly susceptible to cyber attacks by malicious adversaries.