Inexpensive computation and ubiquitous embedded sensing, actuation, and communication provide tremendous opportunities for societal impact, but also great challenges in the design of networked control systems, because the traditional unity feedback loop that operates in continuous time or at a fixed sampling rate is not adequate when sensor data arrives from multiple sources, asynchronously, delayed, possibly corrupted, and — especially important for this project — the different entities that participate in the control system do not share a common clock.

Computer modeling and simulation for medical device evaluation has been pursued as a means for reducing the cost and scope of clinical trials while minimizing the risk of unforeseen adverse outcomes. Advances in computational technologies and algorithms have further enabled analysis with complex and realistic Bayesian models to be applied to clinical trials.

Robust Linear Temporal Logic (rLTL) was crafted to incorporate the notion of robustness into Linear-time Temporal Logic specifications. Robustness is ubiquitous in control systems and translates the intuitive notion that “small” violations of environment assumptions should only lead to “small” violations of system guarantees. This notion was formalized in the logic rLTL via 5 different truth values and it led to an increase in the time complexity of the associated model checking problem.

Abstract: The research objective of this project is to bridge two disparate paths to the control of hybrid dynamical systems—namely, symbolic model-based and Lyapunov analysis-based approaches—via convex programming in order to address major challenges in hybrid control. The primary goal is to establish nonconservative, robust, and scalable control theories and algorithms for verifying/achieving desired stability and performance bounds for hybrid affine systems.

Abstract: Buildings in the U.S. contribute to 39% of energy use, consume approximately 70% of the electricity, and account for 39% of CO2 emissions. Hence, developing green building architec- tures is an extremely critical component in energy sustainability. The investigators will develop a unified analytical approach for green building design that comprehensively manages energy sustainability by taking into account the complex interactions between these systems of systems, providing a high degree of security, agility and robust to extreme events.

Abstract: The research objective of this project is to bridge two disparate paths to the control of hybrid dynamical systems—namely, symbolic model-based and Lyapunov analysis-based approaches—via convex programming in order to address major challenges in hybrid control. Hybrid systems are characterized by the presence of both continuous dynamics and discrete logic that interact with each other.

Abstract: This project addresses the impact of the integration of renewable intermittent generation and the integration of sophisticated sensing, communication, and actuation capabilities into the grid on the system’s reliability, volatility, and economic efficiency, and seeks to develop system architectures, along with associated optimization and control algorithms to balance such trade-­‐offs. The high level goals of this project can be stated as follows:

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