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作者：Casini, Marco; Garulli, Andrea; Vicino, Antonio
作者单位：University of Siena
摘要：State estimation for discrete-time linear systems with uniformly quantized measurements is addressed. By exploiting the set-theoretic nature of the information provided by the quantizer, the problem is cast in the set membership estimation setting. Assuming the possibility of suitably tuning the quantizer range and resolution, the optimal design of adaptive quantizers is formulated in terms of the minimization of the radius of information associated to the state estimation problem. The optimal...
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作者：Deng, Yunshan; Xia, Yuanqing; Sun, Zhongqi; Li, Chang; Hu, Rui
作者单位：Beijing Institute of Technology; Zhongyuan University of Technology
摘要：In this article, we propose a model predictive control (MPC) algorithm using sequential convex programming (SCP) to address concave inequality constraints. Based on traditional SCP, we introduce two methods to improve the solution quality and reduce the cost when SCP is stopped early at each time step. First, we analyze multiple explicit representations of a single constraint and propose a method to reduce convexification loss without solving additional nested dual problems. Second, we map the...
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作者：Hu, Jiang; Zhang, Jiaojiao; Deng, Kangkang
作者单位：University of California System; University of California Berkeley; Royal Institute of Technology; National University of Defense Technology - China
摘要：Decentralized optimization often relies on achieving consensus among disparate agents. This article addresses the consensus problem in decentralized networks, focusing on the challenges posed by a nonconvex compact submanifold constraint. We identify conditions on network topology that facilitate local linear convergence to global consensus, where the achieved linear rate matches that of the Euclidean setting. Central to our analysis are the convex-like properties, specifically proximal smooth...
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作者：Zhang, Peihan; Rathnayake, Bhathiya; Diagne, Mamadou; Krstic, Miroslav
作者单位：University of California System; University of California San Diego; University of California System; University of California San Diego
摘要：For stabilizing stop-and-go oscillations in traffic flow by actuating a variable speed limit (VSL) at a downstream boundary of a freeway segment, we introduce event-triggered partial differential equation (PDE) backstepping designs employing the recent concept of performance-barrier event-triggered control (P-ETC). Our design is for linearized hyperbolic Aw-Rascle-Zhang (ARZ) PDEs governing traffic velocity and density. Compared to continuous feedback, ETC provides a piecewise-constant VSL com...
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作者：Chang, Zeze; Jiao, Junjie; Li, Zhongkui
作者单位：Peking University; Technical University of Munich
摘要：This article considers a localized data-driven consensus problem for leader-follower multiagent systems with unknown discrete-time agent dynamics, where each follower computes its local control gain using only their locally collected state and input data. Both noiseless and noisy data-driven protocols are presented to achieve leader-follower consensus, by addressing the challenge of the heterogeneity in control gains caused by the localized data sampling and distinct parameters of agents. The ...
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作者：Sun, Qingdong; Yang, Guang-Hong
作者单位：Northeastern University - China; Northeastern University - China
摘要：This article studies the secure state estimation problem of continuous-time cyber-physical systems affected by sensor attacks and actuator faults, where the attackers do not target fixed transmission channels but instead stochastically select the channels to attack at each moment based on a specific Markov process. To address these challenges, a reduced-order observer is designed to simultaneously estimate the original system states, faults, and attacks, while ensuring that its observation err...
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作者：Xu, Yong; Wu, Zheng-Guang
作者单位：Beijing Institute of Technology; Zhejiang University
摘要：This article investigates the adaptive optimal output regulation of completely unknown linear time-invariant systems. First, a dynamic state feedback control policy with assured convergence rate requirement is developed such that the output regulation problem is transformed into a tractable optimization problem by incorporating the internal model. Then, an online-verifiable initial excitation-based dual-integrator-based learning algorithm is first proposed for establishing data-driven learning...
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作者：Shah, Suhail M.; Bollapragada, Raghu
作者单位：University of Texas System; University of Texas Austin
摘要：Decentralized optimization is typically studied under the assumption of noise-free transmission. However, real-world scenarios often involve the presence of noise due to factors such as additive white Gaussian noise channels or probabilistic quantization of transmitted data. These sources of noise have the potential to degrade the performance of decentralized optimization algorithms if not effectively addressed. In this article, we focus on the noisy communication setting and propose an algori...
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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...
