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作者：Tian, Kaixin; Mei, Jie; Tian, Congcong; Ma, Guangfu
作者单位：Harbin Institute of Technology; Harbin Institute of Technology; Zhengzhou Tobacco Research Institute of CNTC
摘要：This article focuses on the interval consensus problem, which is characterized by the constraint that each agent has a lower and upper bound on the achievable consensus value. Such constraint is realized by setting saturation for neighbors' positions in agent dynamics. By using a novel system transformation, the heterogeneous high-order interval consensus problem then can be transformed into a first-order one, thus restoring the monotonic property, and further facilitating the analysis of the ...
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作者：Wang, Linyang; Zhu, Bin; Liu, Wanquan
作者单位：Sun Yat Sen University
摘要：Factor analysis is a widely used modeling technique for stationary time series, which achieves dimensionality reduction by revealing a hidden low-rank plus sparse structure of the covariance matrix. Such an idea of parsimonious modeling has also been important in the field of systems and control. In this article, a nonconvex nonsmooth optimization problem involving the l(0) norm is constructed in order to achieve the low-rank and sparse additive decomposition of the sample covariance matrix. W...
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作者：Basilio, Joao C.; Silva, Guilherme M. Ottoni
作者单位：Universidade Federal do Rio de Janeiro
摘要：Studies carried out in real plants have shown thatrepeated and/or intermittent fault events occur frequently duringthe operation of a system. Regarding the occurrence of repeatedfault events, the problem becomes that of determining the numberof occurrences of the fault event, namely, for a given kappa is an element of Z & lowast;+,and based on the observation of events, be sure that the faultevent has occurred at least kappa times (kappa-diagnosability). In thisarticle, the problem of repeated...
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作者：Li, Qiang; Wai, Hoi-To
作者单位：Chinese University of Hong Kong
摘要：This article studies the effect of data homogeneity on multiagent stochastic optimization. We consider the decentralized stochastic gradient (DSGD) algorithm and perform a refined convergence analysis. Our analysis is explicit on the similarity between Hessian matrices of local objective functions, which captures the degree of data homogeneity. We illustrate the impact of our analysis through studying the transient time, defined as the minimum number of iterations required for a distributed al...
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作者：Zhang, Ruichang; Liu, Zhixin; Chen, Ge; Mei, Wenjun
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Peking University
摘要：The Friedkin-Johnsen (FJ) model introduces prejudice into the opinion evolution and has been successfully validated in many practical scenarios; however, due to its weighted average mechanism, only one prejudiced agent can always guide all unprejudiced agents synchronizing to its prejudice under the connected influence network, which may not be in line with some social realities. To fundamentally address the limitation of the weighted average mechanism, a weighted-median opinion dynamics has b...
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作者：Petri, Elena; Postoyan, Romain; Astolfi, Daniele; Nesic, Dragan; Andrieu, Vincent
作者单位：Eindhoven University of Technology; Centre National de la Recherche Scientifique (CNRS); Universite de Lorraine; Universite Claude Bernard Lyon 1; Centre National de la Recherche Scientifique (CNRS); University of Melbourne
摘要：Various methods are nowadays available to design observers for broad classes of systems, where the primary focus is on establishing the convergence of the estimated states. Nevertheless, the question of the tuning of the observer to achieve satisfactory estimation performance remains largely open. In this context, we present a general design framework for the online tuning of the observer gains. Our starting point is a robust nominal observer designed for a general nonlinear system, for which ...
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作者：Rezaeinia, Pouya; Gharesifard, Bahman; Linder, Tamas
作者单位：Queens University - Canada; University of California System; University of California Los Angeles
摘要：In this article, we consider a distributed optimization problem for the sum of convex functions where the underlying communication network connecting nodes at each time epoch is drawn at random from a collection of directed graphs. We propose a modified version of the subgradient-push algorithm that provably almost surely converges to an optimizer on any such sequence of random directed graphs. We also prove that the convergence rate of our proposed algorithm is upper bounded as O(1/root t), w...
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作者：Liu, Lupeng; Lu, Maobin; Wang, Shimin; Deng, Fang; Chen, Jie
作者单位：Beijing Institute of Technology; Massachusetts Institute of Technology (MIT); Beijing Institute of Technology; Tongji University
摘要：In this article, we address the robust distributed Nash equilibrium seeking problem of N-player games under switching networks and communication delays. The salient feature of this work is that the switching communication networks can be uniformly strongly connected, and the communication delays are allowed to be arbitrarily unknown, time-varying and bounded. To solve the problem, we construct a distributed estimator for each player to estimate all players' strategies through unreliable commun...
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作者：Wan, Fangzhe; Zhao, Xueyan; Deng, Feiqi; Huang, Yongjia
作者单位：South China University of Technology
摘要：In this article, the design of periodically intermittent controller (PIC) using sampled-data feedback for hybrid stochastic delay systems (SDSs) with asynchronous switching is studied. This article can be divided into two parts. First, the design of sampled-data-based controllers (SDBCs) via lifting technique (LT) for SDSs with asynchronous switching is discussed. Then, for SDSs with SDBCs, this article takes a further step to design sampled-data-based PIC, which is also based on the LT. For S...
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作者：Fan, Yuzhen; Zhang, Xiaoyu; Gao, Chuanhou; Dochain, Denis
作者单位：Zhejiang University; Southeast University - China; Universite Catholique Louvain
摘要：Neural network related machine learning algorithms, inspired by biological neuron interaction mechanisms, are advancing rapidly in the field of computing. This development may be leveraged in reverse to advance synthetic biology progress. A challenging exploration is to implement neural network functionalities through biochemical reaction networks (BCRNs), a language that is inherently compatible with in vivo, with difficulties specifically in constructing an appropriate BCRN that respects com...
