IEEE Transactions on Automatic Control

最新文章

• Performance Analysis of Distributed Filtering Under Misspecified Noise Covariances AI翻译
  作者：Lyu, Xiaoxu; Wen, Guanghui; Shi, Ling; Duan, Peihu; Duan, Zhisheng
  作者单位：Hong Kong University of Science & Technology; Southeast University - China; Hong Kong University of Science & Technology; Beijing Institute of Technology; Peking University
  摘要：This article systematically investigates the performance of the consensus-based distributed filter under misspecified noise covariances. First, we introduce four quantities: the nominal filter parameter, the nominal estimation error covariance, the ideal filter parameter, and the ideal estimation error covariance. We derive the difference expressions among these quantities and establish the corresponding one-step relations. These relations reveal how performance deteriorates when noise covaria...
• Adaptive Nonlinear Prescribed-Time Control With Filterless Least Squares AI翻译
  作者：Li, Wuquan; Krstic, Miroslav
  作者单位：Ludong University; University of California System; University of California San Diego
  摘要：For linearly parametrized nonlinear systems in normal form, we first develop a new prescribed-time (PT) least-squares identification scheme (abbreviated PT-LS) characterized by a blow-up function, and then design a new PT adaptive controller which ensures that the plant state is regulated to zero in the prescribed time and the parameter estimate converges to a vector-valued constant in the same PT. Under a moderate interval excitation (IE) condition where the IE is fulfilled at the time strict...
• On Uniform Observability of Linear Time-Varying Systems With Respect to Subspaces and Its Applications AI翻译
  作者：Liu, Tao; Huang, Jie
  作者单位：Southern University of Science & Technology; Chinese University of Hong Kong
  摘要：Recently, the notion of uniform observability with respect to a subspace was proposed in (Xia et al., 2022) and was utilized to solve the synchronization problem for single-integrator multiagent systems with time-varying matrix-weighted couplings. This article further explores the concept of uniform observability of a linear time-varying system with respect to a subspace. We will first establish the invariance property of uniform observability with respect to some invariant subspace under time...
• Distributed Cutting Plane Method via Sample Point Consensus AI翻译
  作者：Zhong, Tianyi; Angeli, David
  作者单位：Imperial College London; University of Florence
  摘要：This article considers a general setup for the constrained convex optimization problem over jointly fully connected time-varying networks. We propose a novel cutting plane-based method that embeds a proximity-based consensus scheme for solving this (potentially nonsmooth) optimization problem. The consensus mechanism allows agents to select the same sample point and therefore reconstruct the centralized cut individually. Under convexity, we prove that agents' sample points converge to the opti...
• Contraction Analysis of Time-Varying DAE Systems via Auxiliary ODE Systems AI翻译
  作者：Yin, Hao; Jayawardhana, Bayu; Trenn, Stephan
  作者单位：University of Groningen
  摘要：This article studies the contraction property of time-varying differential-algebraic equation (DAE) systems by embedding them to higher dimension ordinary differential equation (ODE) systems. The first result pertains to the equivalence of the contraction of a DAE system and the uniform global exponential stability of its variational DAE system. Such equivalence inherits the well-known property of contracting ODE systems on a specific manifold. Subsequently, we construct an auxiliary ODE syste...
• Locally Differentially Private Gradient Tracking for Distributed Online Learning Over Directed Graphs AI翻译
  作者：Chen, Ziqin; Wang, Yongqiang
  作者单位：Clemson University
  摘要：Distributed online learning has been proven extremely effective in solving large-scale machine learning problems over streaming data. However, information sharing between learners in distributed learning also raises concerns about the potential leakage of individual learners' sensitive data. To mitigate this risk, differential privacy, which is widely regarded as the gold standard for privacy protection, has been widely employed in many existing results on distributed online learning. However,...
• Bounded Extremum Seeking for Static Quadratic Maps Using Nonlinear Transformation and Lyapunov Method AI翻译
  作者：Mazenc, Frederic; Malisoff, Michael; Fridman, Emilia
  作者单位：Centre National de la Recherche Scientifique (CNRS); Universite Paris Saclay; Louisiana State University System; Louisiana State University; Tel Aviv University
  摘要：We present a new practical stability analysis for a bounded gradient based extremum seeking problem for two variable static quadratic maps that contain a time-varying additive measurement uncertainty. Instead of using earlier averaging-based approaches, we introduce a new state transformation, a time-varying quadratic Lyapunov function, and a comparison principle to obtain essentially less conservative bounds on the dither frequency and on the ultimate bound of the estimation error compared wi...
• Risk-Constrained LQR Design Framework for Non-Gaussian Interconnected Systems Defined Over a Digraph AI翻译
  作者：Wang, Yan; Lv, Mingsong; Wu, Zhiying; Xu, Yunjian; Guan, Nan; Su, Rong
  作者单位：Harbin Institute of Technology; Hong Kong Polytechnic University; Chinese Academy of Sciences; Chinese University of Hong Kong; The Chinese University of Hong Kong, Shenzhen; CUHK Shenzhen Research Institute; City University of Hong Kong; Nanyang Technological University
  摘要：This article studies the risk-constrained linear-quadratic regulation (Rc-LQR) for a class of interconnected systems (ISs) with non-Gaussian noise. The IS is of a weakly connected topology. The standard linear-quadratic regulation (LQR) controller is optimal in expectation for the quadratic cost and, thus, is called risk-neutral LQR (Rn-LQR) controller. However, the Rn-LQR system may suffer from low-probability yet statistically significant/risky events. The Rc-LQR controller can well trade be...
• An Active Learning Method for Solving Competitive Multiagent Decision-Making and Control Problems AI翻译
  作者：Fabiani, Filippo; Bemporad, Alberto
  作者单位：IMT School for Advanced Studies Lucca
  摘要：To identify a stationary action profile for a population of competitive agents, each executing private strategies, we introduce a novel active-learning scheme where a centralized external observer (or entity) can probe the agents' reactions and recursively update simple local parametric estimates of the action-reaction mappings. Under very general working assumptions (not even assuming that a stationary profile exists), sufficient conditions are established to assess the asymptotic properties ...
• On the Equivalence of Model-Based and Data-Driven Approaches to the Design of Unknown-Input Observers AI翻译
  作者：Disaro, Giorgia; Valcher, Maria Elena
  作者单位：University of Padua
  摘要：In this article, we investigate a data-driven approach to the design of an unknown-input observer (UIO). Specifically, we provide necessary and sufficient conditions for the existence of a UIO for a discrete-time linear time-invariant system, designed based only on some available data, obtained on a finite time window. We also prove that, under weak assumptions on the collected data, the solvability conditions derived by means of the data-driven approach are in fact equivalent to those obtaine...