Differentially Private LQ Control

• 成果类型: Article
• 署名作者: Yazdani, Kasra; Jones, Austin; Leahy, Kevin; Hale, Matthew
• 署名单位: State University System of Florida; University of Florida; Massachusetts Institute of Technology (MIT); Lincoln Laboratory
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3148710
• 发表日期: 2023
• 页码: 1061-1068
• 关键词: privacy; Differential privacy; trajectory; COSTS; Power system stability; STANDARDS; GUIDELINES; multiagent systems; network control; privacy

摘要

As multi-agent systems proliferate and more user data, new approaches are needed to protect sensitive data while still enabling system operation. To address this need, this article presents a private multiagent LQ control framework. Agents' state trajectories can be sensitive, and we therefore protect them using differential privacy. We quantify the impact of privacy along three dimensions: the amount of information shared under privacy, the control-theoretic cost of privacy, and the tradeoffs between privacy and performance. These analyses are done in conventional control-theoretic terms, which we use to develop guidelines for calibrating privacy as a function of system parameters. Numerical results indicate that system performance remains within desirable ranges, even under strict privacy requirements.