UC San Diego

Recent technological advances in networking, communication, and computation technologies have enabled the development of cyber-physical systems and cloud robotics, where computing, communication, and control are tightly coupled and integrated into a single distributed platform. These systems open the door to a myriad of new and exciting applications in transportation, health care, agriculture, energy, and many others. The need for the tight integration of different components, requirements, and time scales means that the modeling, analysis, and design of these systems present new challenges. We focus on two aspects of emerging systems architecture. Firstly, we investigate the presence of finite-rate, digital communication channels with delays in the feedback loop. In this context, we study event-triggering strategies that utilize timing information by transmitting in a state-dependent fashion. The proposed event-triggering strategies utilize the available communication resources more efficiently compared to existed time-triggering setups. Secondly, the distributed nature of cyber-physical systems and cloud robotics is their Achilles’ heel, as it is a source of vulnerability to cyber-attacks. In this regard, we introduce the problem of learning-based attacks in these systems, and we show how the controller can impede these attacks by superimposing a carefully crafted privacy-enhancing signal upon its control policy.