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作者：Shi, Xinli; Wen, Guanghui; Cao, Jinde; Yu, Xinghuo
作者单位：Southeast University - China; Southeast University - China; Royal Melbourne Institute of Technology (RMIT)
摘要：In distributed optimization (DO), the designed algorithms are expected to have a fast convergence rate but less computation cost. Moreover, the boundedness of the control inputs is generally required for practical networking agent systems with actuator limitations. Motivated by these observations, we first revisit the well-known finite-time distributed average tracking (FTDAT) problem where a novel sufficient condition on the control gain and the finite settling time estimation are derived bas...
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作者：Sinyakov, Vladimir; Girard, Antoine
作者单位：Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS)
摘要：In this article, we consider the problem of the computation of efficient symbolic abstractions for continuous-time control systems. The new abstraction algorithm builds symbolic models with the same number of states but fewer transitions in comparison to the one produced by the standard algorithm. At the same time, the new abstract system is at least as controllable as the standard one. The proposed algorithm is based on the solution of a region-to-region control synthesis problem. This soluti...
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作者：Liu, Changxin; Zhou, Zirui; Pei, Jian; Zhang, Yong; Shi, Yang
作者单位：University of Victoria; Huawei Technologies; Simon Fraser University
摘要：Decentralized optimization, particularly the class of decentralized composite convex optimization (DCCO) problems, has found many applications. Due to ubiquitous communication congestion and random dropouts in practice, it is highly desirable to design decentralized algorithms that can handle stochastic communication networks. However, most existing algorithms for DCCO only work in networks that are deterministically connected during bounded communication rounds, and therefore, cannot be exten...
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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：Distributed optimization enables networked agents to cooperatively solve a global optimization problem. Despite making significant inroads, most existing results on distributed optimization rely on noise-free information sharing among the agents, which is problematic when communication channels are noisy, messages are coarsely quantized, or shared information are obscured by additive noise for the purpose of achieving differential privacy. The problem of information-sharing noise is particular...
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作者：Xie, Junyao; Humaloja, Jukka-Pekka; Koch, Charles Robert; Dubljevic, Stevan
作者单位：University of Alberta; University of Alberta
摘要：In this article, we address the constrained output estimation of discrete-time linear distributed parameter systems in the presence of plant and measurement disturbances. Sufficient conditions are proposed for the strong stability of the proposed moving horizon estimator. We further show that the discrete-time estimation results can be linked to continuous-time infinite-dimensional systems described by partial differential equations with unbounded disturbance and output operators by using the ...
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作者：Ge, Pudong; Li, Peng; Chen, Boli; Teng, Fei
作者单位：Imperial College London; Harbin Institute of Technology; University of London; University College London
摘要：The robust distributed state estimation for a class of continuous-time linear time-invariant systems is achieved by a novel kernel-based distributed observer, which, for the first time, ensures fixed-time convergence properties. The communication network between the agents is prescribed by a directed graph in which each node involves a fixed-time convergent estimator. The local observer estimates and broadcasts the observable states among neighbors so that the full-state vector can be recovere...
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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：Mao, Wei; Hu, Junhao; Mao, Xuerong
作者单位：Jiangsu Second Normal University; South Central Minzu University; University of Strathclyde
摘要：For many stochastic hybrid systems in the real world, it is inappropriate to study if their solutions will converge to an equilibrium state (say, 0 by default) but more appropriate to discuss if the probability distributions of the solutions will converge to a stationary distribution. The former is known as the asymptotic stability of the equilibrium state while the latter the stability in distribution. This article aims to determine whether or not a stochastic state feedback control can make ...
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作者：Nortmann, Benita; Mylvaganam, Thulasi
作者单位：Imperial College London; Imperial College London
摘要：Considering discrete-time linear time-varying systems with unknown dynamics, controllers guaranteeing bounded closed-loop trajectories, optimal performance, and robustness to process and measurement noise are designed via convex feasibility and optimization problems involving purely data-dependent linear matrix inequalities. For the special case of periodically time-varying systems, infinite-horizon guarantees are achieved based on finite-length data sequences.
