This project aims to investigate energy and delay sensitive sensing, communication, decision-making and control in the context of cyber physical systems. We particularly focus on systems where sensors with varying accuracy observe heterogeneous source signals that must be processed and communicated and used for inference and decision-making purposes.

There is an increased research trend towards the application of distributed control algorithms for network power system control. We analyze the vulnerability of these distributed control algorithms to a potential attack on the communication network. We show that that the decentralized load-side control algorithm for frequency regulation in power system is fragile to communication channel uncertainty. We also propose an optimization-based framework for the design of distributed load-side control algorithm robust to communication channel uncertainty.

This CPS project is driven by largescale online multimodal transit feeds to achieve equilibrium in demand and supply relationship in transportation CPS systems through cyber-control.

The project is developing novel architectures for control and diagnosis of complex cyber-­‐physical  systems  subject to stringent performance  requirements  in  terms  of safety, resilience, and adaptivity. These ever-­‐increasing demands necessitate the use of    formal    model-­‐based    approaches    to    synthesize    provably-­‐correct    feedback controllers.

Design of cyber-physical systems today relies on executable models. Designers develop models, simulate them, nd defects, and improve their designs before the system is built, thus greatly reducing the design costs. However, current model-based design methods lack support for model libraries (creating and exchanging models as "black boxes"), tool interoperability (allowing models to be co-simulated by multiple tools), and multi-view modeling (allowing to combine models that "live in different worlds", for instance, a control-logic model with an energy-consumption model).

The artificial pancreas (AP) is a set of increasingly sophisticated devices and algorithms that will automate the delivery of insulin to patients with type-1 diabetes. While the AP concept promises to alleviate the burden posed by the self-management of blood glucose levels, it also poses significant risks arising from a combination of external disturbances such as patient meals, physical activity, sensor errors, network delays and physiological variations.

Our proposal’s main objective is to realize cyber-physical platform and principles for (i) interrogating global modalities of intracellular transport with causative factors isolated at the single-molecule scale and (ii) realizing efficient and robust infrastructure for transporting micron/molecular scale cargo using distributed strategies We are realizing in-vitro, a transport network with roadways formed by microtubules where motorproteins, kinesin and dynein, will form vehicles ferrying cargo.

Despite many advances in vehicle automation, much remains to be done: the best autonomous vehicle today still lags behind human drivers, and connected vehicle (V2V) and infrastructure (V2I) standards are only just emerging. In order for such cyber-­‐physical systems to fully realize their potential, they must be capable of exploiting one of the richest and most complex abilities of humans, which we take for granted: seeing and understanding the visual world.

Assistive machines, like robot arms mounted on powered wheelchairs, promote independence and ability in those with severe motor impairments. Users of these assistive robots can teleoperate their devices to perform activities of daily living like eating and self care. However, as these machines become more capable, they often also become more complex. Traditional teleoperation interfaces cover only a portion of the control space, and it is necessary to switch between di erent control modes to access the full control space.

Cyber-Physical Systems (CPS) are being increasingly deployed in critical infrastructures such as electric-power, water, transportation, and other networks. These deployments are facilitating real-time monitoring and closed-loop control by exploiting the advances in wireless sensor-actuator networks, the internet of “everything,” data-driven analytics, and machine-to-machine interfaces. CPS operations depend on the synergy of computational and physical components.