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作者：Lin, Peng; Zeng, Chuyu; Zhang, Jinhui; Xia, Yuanqing
作者单位：Central South University; Beijing Institute of Technology
摘要：As is well known, it is challenging to address the convergence for distributed constrained optimization problem, in particular when nonconvex constraints, nonuniform step-sizes (nonuniform gradient gains), and switching graphs are involved. In this article, we study the distributed constrained optimization problem in the presence of five kinds of nonlinearities caused by nonconvex control input constraints, nonconvex interaction constraints, nonuniform step-sizes, nonuniform convex state const...
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作者：Chen, Siyu; Na, Jing; Huang, Yingbo; Xing, Yashan; Zhao, Jing; Wong, Pak Kin
作者单位：Kunming University of Science & Technology; University of Macau
摘要：It has been well known that the learning gain plays a crucial role in the adaptive parameter estimation (APE) for guaranteeing fast convergence and robustness. However, the tuning of learning gains in the existing methods is generally empirical and time-consuming. To address this issue, this article presents a novel APE approach to explore the optimality principle in the design of adaptive laws to obtain an online updated optimal learning gain, which is derived to minimize a cost function of e...
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作者：Ji, Zhengping; Zhang, Xiao; Cheng, Daizhan
作者单位：Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Hong Kong Polytechnic University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
摘要：We propose a method that combines aggregation and bisimulation to approximate large finite-valued networks by smaller models. With the algebraic state-space representation of a quotient system under observational equivalence, the aggregated bisimulation is performed by partitioning a network into blocks and replacing the dynamics of each block by that of its quotient system. If the aggregation is not a bisimulation, these quotient systems can be further replaced by probabilistic networks based...
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作者：Mlinaric, Petar; Beattie, Christopher A.; Drmac, Zlatko; Gugercin, Serkan
作者单位：Virginia Polytechnic Institute & State University; University of Zagreb; Virginia Polytechnic Institute & State University; Virginia Polytechnic Institute & State University
摘要：The iterative rational Krylov algorithm (IRKA) is a commonly used fixed point iteration developed to minimize the H-2 model order reduction error. In this work, the IRKA is recast as a Riemannian gradient descent method with a fixed step size over the manifold of rational functions having fixed degree. This interpretation motivates the development of a Riemannian gradient descent method utilizing as a natural extension variable step size and line search. Comparisons made between the IRKA and t...
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作者：Tang, Jennifer; Adler, Aviv; Ajorlou, Amir; Jadbabaie, Ali
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Analog Devices, Inc.
摘要：Social networks often exert social pressure, causing individuals to adapt their expressed opinions to conform to their peers. An agent in such systems can be modeled as having an (true and unchanging) inherent belief while broadcasting a declared opinion at each time step based on his/her inherent belief and the past declared opinions of his/her neighbors. An important question in this setting is parameter estimation: how to disentangle the effects of social pressure to estimate inherent belie...
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作者：Wu, Jinxian; Dai, Li; Xia, Yuanqing
作者单位：Beijing Institute of Technology
摘要：This article proposes an iterative distributed model predictive control (DMPC) algorithm for multiple dynamically decoupling linear systems subject to both local state and input constraints, as well as coupling constraints that may be nonconvex (e.g., collision avoidance constraints). This issue has not been extensively explored, particularly in the context of allowing flexible termination of inner optimization problem calculations in accordance with the sample time. In this article, we presen...
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作者：Cabral, Leonardo; Valmorbida, Giorgio; da Silva Jr, Joao Manoel Gomes
作者单位：Universidade Federal do Rio Grande do Sul; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); Inria; Universidade Federal do Rio Grande do Sul
摘要：In this article, we study the regional stability of discrete-time piecewise affine (PWA) systems. The proposed method for the stability analysis uses an implicit representation of PWA systems based on ramp functions, and it builds upon Linear Matrix Inequalities to verify the nonnegativity of piecewise quadratic (PWQ) functions in a given set. Verifying the nonnegativity of PWQ functions allows us to solve Lyapunov inequalities yielding a PWQ Lyapunov function of which a level set gives an est...
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作者：Zhou, Shuaiyu; Wei, Yiheng; Cao, Jinde; Liu, Yang
作者单位：Southeast University - China; Ahlia University Bahrain; Zhejiang Normal University
摘要：The prescribed-time convergence mechanism has garnered significant attention within the fields of optimization and control, primarily attributed to its ability for precise manipulation of target completion times. This article formulates sliding manifolds with prescribed-time stability, based on which two modified zero-gradient-sum (ZGS) algorithms are established. One of the optimization algorithms is developed based on a multistage structural framework and another is based on a single-stage o...
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作者：Varley, Maxwell M.; Molloy, Timothy L.; Nair, Girish N.
作者单位：University of Melbourne; Australian National University
摘要：Systems equipped with modern sensing modalities such as vision and Lidar gain access to increasingly high-dimensional measurements with which to enact estimation and control schemes. In this article, we examine the continuum limit of high-dimensional measurements and analyze state estimation in linear time-invariant systems with infinite-dimensional measurements but finite-dimensional states, both corrupted by additive noise. We propose a linear filter and derive the corresponding optimal gain...
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作者：Luo, Jialei; Liu, Wei
作者单位：South China University of Technology
摘要：In this article, we consider the leader-following consensus problem with prescribed performance for general linear multiagent systems. To solve this problem, we construct a distributed state feedback control law on the basis of some barrier Lyapunov functions. Then, all the consensus errors are proved to converge to zero asymptotically and the time-varying prescribed performance is proved to be achieved. Finally, we give a simulation example to confirm our results.
