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.

Recently there is an increasing availability of smart wearables including smart watches, bands, buttons and pendants. Many of these devices are part of human-in-the-loop Cyber Physical Systems (CPS). With future fundamental advances in the intersection of communications, control, and computation for these energy and resource limited devices, there is a great potential to revolutionize many CPS applications.

Millions of mobile applications (apps) are being developed in domains such as energy, health, security, and entertainment. The US FDA expects that there will be 500 million smart phone users downloading healthcare related apps by the end of 2015. Many of these apps will perform interventions to control human physiological parameters such as blood pressure and heart rate. The intervention aspects of the apps can cause dependency problems, e.g., multiple interventions of multiple apps can increase or decrease each other’s effects, some of which can be harmful to the user.

Cyber-Physical Systems (CPS) that contain self-modifying smart components can improve and self-repair, but sometimes at the cost of impeding model-based Verification and Validation (V&V).  In this work, we focus on maintaining short and long range V&V capability in a system containing self-adaptive smart components. In this work, we focus on smart component based in-flight control adaptation of damaged Flapping-Wing Micro Air Vehicles (FW-MAV).

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

Many safety-critical cyber-physical systems rely on advanced sensing capabilities to react to changing environmental conditions. However, cost-effective deployments of such capabilities have remained elusive. Such deployments will require software infrastructure that enables multiple sensor-processing streams to be multiplexed onto a common hardware platform at reasonable cost, as well as tools and methods for validating that required processing rates can be maintained.

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.