Computational simulation is one of the most im- portant ways of reproducing the dynamic responses of a Cyber Physical System using a model of the system. The simulation discovers areas of differential system performance and allows linking such performance back to system characteristics. In the medical domain, patient simulators are used to train physicians in patient management. One critical question is how to verify these systems under realistic human (physician) input.

Modern cyber-physical systems are monitored and controlled by multi-core platforms, and thermal management of multi-core chips is critical as overheated cores thereon will suffer from exponentially decaying lifetime and unacceptable performance degradation. To meet the timing and system lifetime reliability requirements under dynamic workloads and operating environment, we need a real-time thermal management (RTM) scheme that predicts run-time temperature and actuates effective thermal control without compromising task deadlines.

Recent progress in battery technology has made it possible to use batteries to power various physical platforms, such as ground/air/water vehicles. These platforms require hundreds/thousands of battery cells to meet their power and energy needs. Of these, automobiles, locomotives, and unmanned air vehicles (UAVs) face the most stringent environmental challenges. In particular, and of special importance to the automotive industry, is the transition from conventional powertrains to (plug-in) hybrid and electric vehicles, all of which are subject to environmental and operational variations.

The overarching project goal is to advance the design of opportunistic state-triggered aperiodic controllers for networked cyber-physical systems.  This poster considers the problem of event-triggered control design for cyberphysical systems with nonlinear dynamics under time-varying input delays.

It's common in controller design to assume that the controller reads the sensors and writes to the actuators at the same time instant. This assumption is often violated in practice because the controller executes its code sequentially on a microprocessor. If the microprocessor is "fast enough," often the controller will still work. However, if the sensing and control are done by two different devices that must communicate across a network, the resulting timing uncertainty due to network delays and clock offsets will often destabilize the controller.

 Despite their importance within the energy sector, buildings have not kept pace with technological improvements and particularly the introduction of intelligent features. A primary obstacle in enabling intelligent buildings is their highly distributed and diffuse nature. To address this challenge, a modular approach will be investigated for building design, construction, and operation that would completely transform the building industry.

The goal of this project is to create a scalable and robust cyber-physical system (CPS) framework for the observation and control of the functional interdependencies between bridge structures (stationary physical systems) and trucks (mobile physical agents). A CPS framework (Figure 1) is being developed to monitor and control trucks within a single highway corridor to manage the imposed loads and the consumption of structural life by trucks on highway infrastructure including bridges. The framework begins with the installation of wireless sensing

Shared hardware resources like caches and memory introduce timing unpredictability for real-time systems. Worst-case execution time (WCET) analysis with shared hardware resources is often so pessimistic that the extra processing capacity of multicore systems is negated. We propose techniques to improve performance and schedulability for multicore systems.

Security and privacy concerns in the increasingly interconnected world are receiving much attention from the research community, policymakers, and general public.  However, much of the recent and on-going efforts concentrate on privacy in communication and social interactions.  The advent of cyber-physical systems, which aim at tight integration between distributed computational intelligence, communication networks, physical world, and human actors, opens new possibilities for developing intelligent systems with new capabilities.