The goal of this project is to create an integrative framework for the design of coupled biological and robotic systems that accommodates system uncertainties and competing objectives in a rigorous, holistic, and effective manner. The design principles are developed using a concrete, end-to-end application of tracking and modeling fish movement with a network of gliding robotic fish.

In recent years, we have seen a number of successful cyber-attacks against high-profile targets, which have demonstrated that resourceful and determined attackers can penetrate even highly secure systems. In light of these attacks, it becomes apparent that defenders of cyber-physical systems cannot focus solely on preventing attackers from penetrating their systems. Instead, they must also prepare to promptly detect and mitigate security breaches, thereby limiting the impact of successful attacks.

Rapid evolution of energy generation technology and increasing usage of distributed energy resources (DER) is pushing utilities to adapt and evolve business models that are aligned with these changes. Energy pricing is becoming rather competitive and transactional, needing utilities to increase flexibility of grid operations and incorporate transactive energy systems (TES). However, a huge bottleneck is to ensure stable grid operations while gaining efficiency. A comprehensive platform is therefore needed for grid-scale multi-aspect integrated evaluations.

Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. This project develops new computer system infrastructure and algorithms for self-sustainable data-driven systems in the field.

A longstanding problem in the design of cyber-physical systems is the inability and ineffectiveness in coping with software and hardware evolutions over the lifetime of a design or across multiple versions in the same product family. The objective of this project is to develop a systematic framework for designing extensible cyber-physical systems that can enable efficient and correct updates with minimal redesign and re-verification efforts.

The overall research objective of the project is to establish and demonstrate a generic motion- sensing co-design procedure that significantly reduces the complexity of mission design for swarm- ing CPS, and greatly facilitates the development of effective and efficient control and sensing strategies.

Many complex engineering systems involve interactions among a large number of agents with coupled dynamics and decisions due to their shared environment and resources. Such systems are often operated using a hierarchical architecture, where a coordinator determines some macroscopic control signal to steer the population to achieve a desired group objective while respecting local preferences and constraints for individual agents. Examples include electricity demand response programs, ground and air transportation systems, data center power management, robotic networks, among others.

The goal of this project is to establish a theoretical and empirical foundation for secured and efficient energy resource management in the smart grid - a typical energy-based cyber-physical system and the future critical energy infrastructure for the nation. In this study, we focus on the detection threats and propose a Gaussian-Mixture Model-based Detection (GMMD) scheme to mitigate data integrity attacks.

This poster exposes the numerous fundamental results that stemmed from this project within the area of cyber-physical systems security.