8期

最新文章

• Distributed Strategy Design for Free-In and Free-Out Aggregative Games AI翻译
  作者：Liu, Yuxuan; Ye, Maojiao; Ding, Lei; Han, Qing-Long
  作者单位：Nanjing University of Science & Technology; Nanjing University of Posts & Telecommunications; Nanjing University of Posts & Telecommunications; Swinburne University of Technology
  摘要：This article proposes a new aggregative game model over free-in and free-out networks, in which each player can freely join and leave the network at its timing and aims to minimize its total cost during its active period. To enable the players to make self-beneficial decisions in such a dynamic environment, it is assumed that the players can locally store and exchange the historical action information. Based on the stored information, a distributed strategy is established, in which each player...
• Duality Between Controllability and Observability for Target Control and Estimation in Networks AI翻译
  作者：Montanari, Arthur N.; Duan, Chao; Motter, Adilson E.
  作者单位：Northwestern University; Northwestern University; Xi'an Jiaotong University; Northwestern University; Northwestern University
  摘要：Output controllability and functional observability are properties that enable, respectively, the control and estimation of part of the state vector. These notions are of utmost importance in applications to high-dimensional systems, such as large-scale networks, in which only a target subset of variables (nodes) is sought to be controlled or estimated. Although the duality between full-state controllability and observability is well established, the characterization of the duality between the...
• A Continuous-Time Violation-Free Multiagent Optimization Algorithm and Its Applications to Safe Distributed Control AI翻译
  作者：Tan, Xiao; Liu, Changxin; Johansson, Karl H.; Dimarogonas, Dimos V.
  作者单位：Royal Institute of Technology
  摘要：In this work, we propose a continuous-time distributed optimization algorithm with guaranteed zero coupling constraint violation and apply it to safe distributed control in the presence of multiple control barrier functions (CBFs). The optimization problem is defined over a network that collectively minimizes a separable cost function with coupled linear constraints. An equivalent optimization problem with auxiliary decision variables and a decoupling structure is proposed. A sensitivity analy...
• Properties of Fundamental Matrix Groups for High-Order Linear Time-Invariant Systems AI翻译
  作者：Wu, Ai-Guo
  作者单位：Harbin Institute of Technology
  摘要：In this article, commutativity-like relations between the fundamental matrix groups and the system matrices are established for high-order continuous-time and discrete-time linear time-invariant systems. With the aid of the commutativity-like properties, alternative proofs of the formulae for state responses are provided for these two classes of high-order linear time-invariant systems.
• Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods With Entropy Regularization AI翻译
  作者：Ding, Yuhao; Zhang, Junzi; Lee, Hyunin; Lavaei, Javad
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley
  摘要：Entropy regularization is an efficient technique for encouraging exploration and preventing a premature convergence of (vanilla) policy gradient (PG) methods in reinforcement learning (RL). However, the theoretical understanding of entropy-regularized RL algorithms has been limited. In this article, we revisit the classical entropy-regularized PG methods with the soft-max policy parametrization, whose convergence has so far only been established assuming access to exact gradient oracles. To go...
• Reduced-Order Consensus Protocols With Pure Relative Output: Design, Existence, and Dual Results AI翻译
  作者：Ma, Yuwen; Li, Xianwei; Li, Shaoyuan; Lin, Zongli
  作者单位：Shanghai Jiao Tong University; Shanghai Jiao Tong University; University of Virginia
  摘要：This article studies reduced-order dynamic consensus protocols for homogeneous linear multiagent systems using pure relative output information. By applying H infinity control theory, a separation principle like method with an additional small-gain constraint is proposed for designing an (n(x)-n(u))th order protocol, where n(x )and n(u )are the numbers of states and inputs of each agent, respectively. Existence conditions for the protocol are then systematically discussed from the graph, low-g...
• Analysis of Input-Affine Dynamical Systems Using Parameterized Robust Counterparts AI翻译
  作者：Miller, Jared; Sznaier, Mario
  作者单位：University of Stuttgart; Northeastern University
  摘要：Common tasks in system analysis and control include optimal control, peak estimation, reachable set estimation, and maximum control invariant set estimation. A standard method to solve these problems is to lift them into infinite-dimensional convex linear programs. However, finite-dimensional truncations of these problems suffer a curse of dimensionality with respect to the size of the state and input. In the case where the dynamical system is input-affine and the input is restricted to a conv...
• Optimal Feedback Control for a Class of Nonlinear Time-Delay Systems AI翻译
  作者：Hu, Hongxiao; Zhou, Zixin; Xu, Liguang; Ding, Zhengtao
  作者单位：University of Shanghai for Science & Technology; University of Shanghai for Science & Technology; University of Manchester
  摘要：This article addresses the problem of optimal nonlinear feedback control for a class of nonlinear time-delay systems over an infinite horizon, involving a nonlinear-nonquadratic performance functional. To this end, we propose a framework for analyzing and designing nonlinear feedback controllers that minimize such cost functionals for these systems. By applying the Lyapunov functional method, the stability of a class of nonlinear time-delay systems is determined over an infinite horizon. This ...
• A Stochastic Surveillance Stackelberg Game: Co-Optimizing Defense Placement and Patrol Strategy AI翻译
  作者：John, Yohan; Diaz-Garcia, Gilberto; Duan, Xiaoming; Marden, Jason R.; Bullo, Francesco
  作者单位：University of California System; University of California Santa Barbara; Shanghai Jiao Tong University
  摘要：Stochastic patrol routing is known to be advantageous in adversarial settings; however, the optimal choice of stochastic routing strategy is dependent on a model of the adversary. We adopt a worst-case omniscient adversary model from the literature and extend the formulation to accommodate heterogeneous defenses at the various nodes of the graph. Introducing this heterogeneity leads to interesting new patrol strategies. We identify efficient methods for computing these strategies in certain cl...
• Gain Scheduling With a Neural Operator for a Transport PDE With Nonlinear Recirculation AI翻译
  作者：Lamarque, Maxence; Bhan, Luke; Vazquez, Rafael; Krstic, Miroslav
  作者单位：Universite PSL; MINES ParisTech; University of California System; University of California San Diego; University of Sevilla
  摘要：To stabilize partial differential equation (PDE) models, control laws typically require space-dependent functional gains mapped by nonlinear operators from the PDE functional coefficients. When a PDE is nonlinear and its pseudocoefficient functions are state-dependent, a gain-scheduling (GS) nonlinear design is the simplest approach to the design of nonlinear feedback.The GS version of PDE backstepping employs gains obtained by solving a PDE at each value of the state. Performing such PDE comp...