IEEE Transactions on Automatic Control

最新文章

• Distributed Output-Feedback Consensus Control of Multiagent Systems with Unknown Output Measurement Sensitivity AI翻译
  作者：Li, Kuo; Hua, Chang-Chun; You, Xiu; Guan, Xin-Ping
  作者单位：Yanshan University; Shanxi University; Shanghai Jiao Tong University
  摘要：This article addresses the leader-following consensus problem for multiagent systems with unknown output measurement sensitivity based on a fixed directed topology. Different from the existing works on the consensus problem, the output measurement sensitivity is described as a total unknown parameter. Under this nonideal condition, we put forward a distributed output-feedback consensus control algorithm for the first time. To start with, we design the novel distributed high-gain observer and a...
• Nash Equilibria for Major-Minor LQG Mean Field Games With Partial Observations of All AI翻译
  作者：Firoozi, Dena; Caines, Peter E.
  作者单位：Universite de Montreal; HEC Montreal; McGill University; McGill University
  摘要：Partially observed major-minor nonlinear and linear quadratic Gaussian (PO MM LQG) mean field game (MFG) systems where the major agent's state is partially observed by each minor agent, and the major agent completely observes its own state have been analyzed in the literature. In this article, PO MM LQG MFG problems with general information patterns are studied where the major agent has partial observations of its own state, and each minor agent has partial observations of its own state and th...
• Max-Min Fair Sensor Scheduling: Game-Theoretic Perspective and Algorithmic Solution AI翻译
  作者：Wu, Shuang; Ren, Xiaoqiang; Hong, Yiguang; Shi, Ling
  作者单位：Hong Kong University of Science & Technology; Shanghai University; Chinese Academy of Sciences
  摘要：We consider the design of a fair sensor schedule for a number of sensors monitoring different linear time-invariant processes. The largest average remote estimation error among all processes is to be minimized. We first consider a general setup for the max-min fair allocation problem. By reformulating the problem as its equivalent form, we transform the fair resource allocation problem into a zero-sum game between a judge and a resource allocator. We propose an equilibrium seeking procedure an...
• Hierarchical Selective Recruitment in Linear-Threshold Brain Networks Part II: Multilayer Dynamics and Top-Down Recruitment AI翻译
  作者：Nozari, Erfan; Cortes, Jorge
  作者单位：University of Pennsylvania; University of California System; University of California San Diego
  摘要：Goal-driven selective attention (GDSA) is a remarkable function that allows the complex dynamical networks of the brain to support coherent perception and cognition. Part I of this two-part article proposes a new control-theoretic framework, termed hierarchical selective recruitment (HSR), to rigorously explain the emergence of GDSA from the brain's network structure and dynamics. This part completes the development of HSR by deriving conditions on the joint structure of the hierarchical subne...
• Bilateral Boundary Control of Moving Shockwave in LWR Model of Congested Traffic AI翻译
  作者：Yu, Huan; Diagne, Mamadou; Zhang, Liguo; Krstic, Miroslav
  作者单位：University of California System; University of California San Diego; Rensselaer Polytechnic Institute; Beijing University of Technology
  摘要：We develop backstepping state feedback control to stabilize a moving shockwave in a freeway segment under bilateral boundary actuations of traffic flow. A moving shockwave, consisting of light traffic upstream of the shockwave and heavy traffic downstream, is usually caused by changes of local road situations. The density discontinuity travels upstream and drivers caught in the shockwave experience transitions from free to congested traffic. Boundary control design in this article brings the s...
• A Control Theoretic Look at Granger Causality: Extending Topology Reconstruction to Networks With Direct Feedthroughs AI翻译
  作者：Dimovska, Mihaela; Materassi, Donatello
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：Reconstructing the causal structure of a network of dynamic systems from observational data is an important problem in many areas of science. One of the earliest and most prominent approaches to this problem is Granger causality. It has been shown that in a network with linear dynamics and strictly causal transfer functions, Granger causality consistently reconstructs the underlying graph of the network. On the other hand, techniques that allow for the presence of direct feedthroughs usually a...
• Incentive Compatibility in Stochastic Dynamic Systems AI翻译
  作者：Ma, Ke; Kumar, P. R.
  作者单位：United States Department of Energy (DOE); Pacific Northwest National Laboratory; Texas A&M University System; Texas A&M University College Station
  摘要：The classic Vickrey-Clarke-Groves (VCG) mechanism ensures incentive compatibility, i.e., truth-telling is a dominant strategy for all agents, for a static one-shot game. However, it does not appear to be feasible to construct mechanisms that ensure dominance of dynamic truth-telling for agents comprised of general stochastic dynamic systems. The agents' intertemporal net utilities depend on future controls and payments, and a direct extension of the VCG mechanism does not guarantee incentive c...
• Nonsmooth Extremum Seeking Control With User-Prescribed Fixed-Time Convergence AI翻译
  作者：Poveda, Jorge, I; Krstic, Miroslav
  作者单位：University of Colorado System; University of Colorado Boulder; University of California System; University of California San Diego
  摘要：This article introduces a new class of nonsmooth extremum seeking controllers (ESCs) with convergence bounds given by class-KL functions that have a uniformly bounded settling time. These ESCs are characterized by nominal average systems that render uniformly globally fixed-time stable (UGFxTS), the set of minimizers of the response map of a stable nonlinear plant. Given that, under suitable tuning of the parameters of the controllers, the ESCs inherit the convergence properties of their avera...
• Delayed Disturbance Attenuation via Measurement Noise Estimation AI翻译
  作者：Furtat, Igor; Fridman, Emilia
  作者单位：Russian Academy of Sciences; Tel Aviv University
  摘要：A novel control law is proposed to attenuate the influence of bounded disturbances and measurement noises for plants with vector output and sector-bounded nonlinearities. The control law is based on the estimation of measurement noises. Differently from the existing results, the ultimate bound of the closed-loop system depends only on one component of the noise vector (as well as on the disturbance). The proposed control law is extended to systems with uncertain input and output delays. The in...
• Continuous-Time Discounted Mirror Descent Dynamics in Monotone Concave Games AI翻译
  作者：Gao, Bolin; Pavel, Lacra
  作者单位：University of Toronto
  摘要：We consider concave continuous-kernel games characterized by monotonicity properties and propose discounted mirror descent type dynamics. We introduce two classes of dynamics whereby the associated mirror map is constructed based on a strongly convex or a Legendre regularizer. Depending on the properties of the regularizer, we show that these new dynamics can converge asymptotically in concave games with merely monotone (negative) pseudogradient. Furthermore, we show that when the regularizer ...