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作者：Kao, Yonggui; Liu, Xiaonan; Song, Minghui; Zhao, Lin; Zhang, Qiang
作者单位：Harbin Institute of Technology; Qingdao University; Shandong Jiaotong University
摘要：This article concerns nonfragile-observer-based integral sliding mode control for a class of uncertain switched hyperbolic systems (USHSs). First, by means of variable substitutions, the original hyperbolic differential system is reduced into a first-order one. Then, a nonfragile observer and the state-estimate-based sliding mode control law are designed, respectively, such that the reachability of the sliding surface and the novel criteria on asymptotical stability of the sliding dynamic USHS...
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作者：Zhang, Gongbo; Chen, Bin; Jia, Qing-Shan; Peng, Yijie
作者单位：Peking University; National University of Defense Technology - China; Tsinghua University
摘要：In this article, we study the problem of selecting a subset with the best of a finite number of alternatives under a fixed simulation budget. Our work aims to maximize the posterior probability of correctly selecting such a subset. We formulate the dynamic sampling decision as a stochastic control problem in a Bayesian setting. In an approximate dynamic programming paradigm, we propose a sequential sampling policy based on value function approximation. We analyze the asymptotic property of the...
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作者：Nguyen, Lien T. T.; Yu, Xinghuo; Eberhard, Andrew; Li, Chaojie
作者单位：Royal Melbourne Institute of Technology (RMIT); Royal Melbourne Institute of Technology (RMIT); University of New South Wales Sydney
摘要：In this article, we propose fixed-time gradient dynamics with time-varying coefficients for continuous-time optimization. We first investigate the Lyapunov stability conditions that allow us to achieve fixed-time stability of the time-varying dynamical systems. We then use them to deal with continuous-time optimization problems. We show that under the proposed fixed-time gradient dynamics and by choosing time-varying coefficients, the searching trajectories converge to their optima in fixed-ti...
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作者：Wang, Yongqiang; Basar, Tamer
作者单位：Clemson University; University of Illinois System; University of Illinois Urbana-Champaign
摘要：By enabling multiple agents to cooperatively solve a global optimization problem in the absence of a central coordinator, decentralized stochastic optimization is gaining increasing attention in areas as diverse as machine learning, control, and sensor networks. Since the associated data usually contain sensitive information, such as user locations and personal identities, privacy protection has emerged as a crucial need in the implementation of decentralized stochastic optimization. In this a...
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作者：Kivits, E. M. M.; van den Hof, Paul M. J.
作者单位：Eindhoven University of Technology
摘要：Physical dynamic networks most commonly consist of interconnections of physical components that can be described by diffusive couplings. These diffusive couplings imply that the cause-effect relationships in the interconnections are symmetric, and therefore, physical dynamic networks can be represented by undirected graphs. This article shows how prediction error identification methods developed for linear time-invariant systems in polynomial form can be configured to consistently identify the...
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作者：Castellano, Agustin; Min, Hancheng; Bazerque, Juan Andres; Mallada, Enrique
作者单位：Johns Hopkins University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：This article puts forward the concept that learning to take safe actions in unknown environments, even with probability one guarantees, can be achieved without the need for an unbounded number of exploratory trials. This is indeed possible, provided that one is willing to navigate tradeoffs between optimality, level of exposure to unsafe events, and the maximum detection time of unsafe actions. We illustrate this concept in two complementary settings. We first focus on the canonical multiarmed...
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作者：Martin, Tim; Allgoewer, Frank
作者单位：University of Stuttgart
摘要：In the context of dynamical systems, nonlinearity measures quantify the strength of nonlinearity by means of the distance of their input-output behavior to a set of linear input-output mappings. In this article, we establish a framework to determine nonlinearity measures and other optimal input-output properties for nonlinear polynomial systems without explicitly identifying a model but from a finite number of input-state measurements, which are subject to noise. To this end, we deduce from da...
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作者：Zeng, Sihan; Doan, Thinh T.; Romberg, Justin
作者单位：University System of Georgia; Georgia Institute of Technology; Virginia Polytechnic Institute & State University
摘要：In this article, we study a decentralized variant of stochastic approximation (SA), a data-driven approach for finding the root of an operator under noisy measurements. A network of agents, each with its own operator and data observations, cooperatively find the fixed point of the aggregate operator over a decentralized communication graph. Our main contribution is to provide a finite-time analysis of this decentralized SA method when the data observed at each agent are sampled from a Markov p...
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作者：Jansch-Porto, Joao Paulo; Hu, Bin; Dullerud, Geir E.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
摘要：Recently, policy optimization has received renewed attention from the control community due to various applications in reinforcement learning tasks. In this article, we investigate the global convergence of the gradient method for quadratic optimal control of discrete-time Markovian jump linear systems (MJLS). First, we study the optimization landscape of direct policy optimization for MJLS, with static-state feedback controllers and quadratic performance costs. Despite the nonconvexity of the...
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作者：Bin, Michelangelo; Astolfi, Daniele; Marconi, Lorenzo
作者单位：Imperial College London; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Engineering & Systems Sciences (INSIS); Universite Claude Bernard Lyon 1; University of Bologna
摘要：Robustness is a basic property of any control system. In the context of linear output regulation, it was proved that embedding an internal model of the exogenous signals is necessary and sufficient to achieve tracking of the desired reference signals in spite of external disturbances and parametric uncertainties. This result is commonly known as the internal model principle. A complete extension of such linear result to general nonlinear systems is still an open problem, exacerbated by the lar...
