-
作者：Chen, Ziqin; Wang, Yongqiang
作者单位：Clemson University
摘要：The increasing usage of streaming data has raised significant privacy concerns in decentralized optimization and learning applications. To address this issue, differential privacy (DP) has emerged as a standard approach for privacy protection in decentralized online optimization. Regrettably, existing DP solutions for decentralized online optimization face the dilemma of trading optimization accuracy for privacy. In this article, we propose a local-DP solution for decentralized online optimiza...
-
作者：Chen, Yan; Fradkov, Alexander L.; Fu, Keli; Fu, Xiaozheng; Li, Tao
作者单位：East China Normal University
摘要：Motivated by distributed statistical learning over uncertain communication networks, we study distributed stochastic optimization by networked nodes to cooperatively minimize a sum of convex cost functions. The network is modeled by a sequence of time-varying random digraphs with each node representing a local optimizer and each edge representing a communication link. In this article, we consider the distributed subgradient optimization algorithm with noisy measurements of local cost functions...
-
作者：Jiang, Yao-Lin; Zhang, Guo-Yun
作者单位：Xi'an Jiaotong University
摘要：Research on nonlinear model order reduction has revealed that as nonlinearity increases, the subspaces capturing dominant information require more complex bases. The complexity is influenced by two main factors: coefficients and approximation criteria. On one hand, it is affected by the characteristics of all coefficients. Therefore, we begin by introducing a generalized Gramian-based method for estimating eigenvalue decay, which demonstrates the factors on the reduced order. On the other hand...
-
作者：Paarporn, Keith; Chandan, Rahul; Alizadeh, Mahnoosh; Marden, Jason R.
作者单位：University of Colorado System; University of Colorado at Colorado Springs; University of California System; University of California Santa Barbara
摘要：In this article, we consider incomplete and asymmetric information formulations of the General Lotto game, which describes two opposing players that strategically allocate limited resources over multiple contests. In particular, we consider scenarios where one of the player's resource budget is common knowledge while the other player's is private. Our main contribution provides complete equilibrium characterizations in the scenario where the private resource budget is drawn from a Bernoulli di...
-
作者：Xie, Gang; Tong, Yin; Wang, Xiaomin; Seatzu, Carla
作者单位：Southwest Jiaotong University; University of Cagliari
摘要：This article studies the supervisory control problem (SCP) of discrete-event systems under sensor attacks. The plant is modeled with a labeled Petri net (LPN) and the attacker has the ability to replace and erase the sensor readings in the communication channel. Our goal is to synthesize a maximally permissive and resilient supervisor for the LPN such that the controlled system satisfies the safety specification under attack. Given a set of safe markings, the basis reachability graph (BRG) for...
-
作者：Jiang, Shuoying; Ding, Zhengtao
作者单位：University of Manchester
摘要：This article investigates the continuous-time optimal distributed coordination problem with resource allocation constraints for general linear multiagent systems. The study is conducted over a connected undirected graph. By integrating the tracking controller design with global resource allocation optimization, fully distributed state-feedback controllers are proposed to solve optimization problems with output-based local objective functions. The dynamics of the entire multiagent system are we...
-
作者：Pan, Guanru; Ou, Ruchuan; Faulwasser, Timm
作者单位：Dortmund University of Technology; Hamburg University of Technology
摘要：The fundamental lemma by J. C. Willems and coauthors enables the representation of all input-output trajectories of a linear time-invariant (LTI) system by measured input-output data. This result has proven to be pivotal for data-driven control. Building on a stochastic variant of the fundamental lemma, this article presents a data-driven output-feedback predictive control scheme for stochastic LTI systems. The considered LTI systems are subject to non-Gaussian disturbances about which only in...
-
作者：Chen, Ziqin; Wang, Yongqiang
作者单位：Clemson University
摘要：Distributed online learning is gaining increased traction due to its unique ability to process large-scale datasets and streaming data. To address the growing public awareness and concern about privacy protection, plenty of algorithms have been proposed to enable differential privacy in distributed online optimization and learning. However, these algorithms often face the dilemma of trading learning accuracy for privacy. By exploiting the unique characteristics of online learning, this article...
-
作者：Li, Nan; Li, Yutong; Kolmanovsky, Ilya
作者单位：Tongji University; Ford Motor Company; University of Michigan System; University of Michigan
摘要：In this note, we propose a supervisory control scheme that unifies the abilities of safety protection and safety extension. It produces a control that keeps the system safe indefinitely when such a control exists. When such a control does not exist, it optimizes the control to maximize the time before any safety violation, which translates into more time to seek recovery and/or mitigate any harm. We describe the scheme and develop an approach that integrates the two abilities into a single con...
-
作者：Wang, Sijian; Yu, Xin
作者单位：Guangxi University
摘要：In this article, we develop a continuous-time algorithm based on a multiagent system for solving distributed, nonsmooth, and pseudoconvex optimization problems with local convex inequality constraints. The proposed algorithm is modeled by differential inclusion, which is based on the penalty method rather than the projection method. Compared with existing methods, the proposed algorithm has the following advantages. First, this algorithm can solve the distributed optimization problem, in which...
