This EArly-concept Grant for Exploratory Research (EAGER) project considers how well-understood control architectures can be modified to produce novel consensus control strategies in the context of privacy protection for engineering networks. Communication and computing capabilities are increasingly being integrated into even the most commonplace items, forming an interconnected network of devices capable of independent and cooperative action. These connected objects can coordinate their actions to improve the efficiency and performance of systems such as smart power grids and automated traffic control systems. However, the widespread sharing of data also risks divulging private information. For example, the exchange of very detailed consumer usage profiles between network operators and dispatch units enables optimized power forecast, generation, and distribution in a smart grid, but also allows others to infer knowledge about the presence, absence, or even the specific activities of a home's occupants. Classical encryption is too slow to be deployed in time-critical engineering applications such as self-driving cars, where carefully tuned controllers generate tens or hundreds of commands per second. The insight developed in this project is that exchanged information, and even control commands, can be obscured by the innovative application of existing control architectures. This project will demonstrate the feasibility of this approach and outline its major features. The results of this project will advance national prosperity by offering the economic advantages of communication and coordination, without violating confidentiality. The research results will be integrated into the graduate curriculum, and into undergraduate research projects supervised by the Principal Investigator.
This project will explore the stabilization of decentralized coordination algorithms under random time-varying coupling weights which will be used for obscuring information. With recent advances in wireless communications and networking, decentralized coordination algorithms have become widespread in networked robots, sensor networks, and intelligent transportation systems. Although their inherent flexibility and scalability make decentralized coordination algorithms appealing for large-scale systems, they also pose significant challenges to privacy protection design. This is because conventional privacy-preserving mechanisms rely on the assistance of a central data aggregator or a trusted third party -- mechanisms that are ruled out in a decentralized implementation. This project builds upon recent results by the Investigator, specifically a privacy-preserving mechanism which obscures information through uncertain time-varying controls. The approach does not need the assistance of any third party and is superior to existing approaches in terms of flexibility, scalability, accuracy, and computation overhead. However, this privacy-preserving approach leads to random time-varying coupling weights, whose influence on decentralized coordination is unclear. This project will address this problem through rigorous analysis of the convergence conditions and speed of decentralized coordination under random time-varying coupling weights. The main thrusts of the project are first to characterize the condition under which nonlinear consensus can be achieved when coupling weights are time-varying and randomly chosen from a certain interval, next to analyze the convergence speed of decentralized coordination under random time-varying coupling weights, and finally to systematically verify obtained results using a multi-robot test bed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
