9期

最新文章

• Feedback Regulation for Max-Plus Linear Systems AI翻译
  作者：Chen, Pengcheng; Zhang, Jiye; Wang, Cailu
  作者单位：Yanshan University; Yanshan University
  摘要：This note investigates the feedback regulation of reducible max-plus linear systems with m inputs and n outputs. The aim is to design a regulator that ensures the system directly reaches a uniform periodic steady state from any initial input, bypassing any transient phase. The normalized projector is proposed to construct the feedback regulator for reducible systems. The regulator synchronizes the eigenvalues of all irreducible blocks to spectral radius of system matrix. In addition, the poles...
• Improved Lyapunov Stability Criteria of Delay Systems and Application to Uncertain Complex Networks: New Uncertainty Estimation Method AI翻译
  作者：Kong, Fanchao; Song, Yongduan; Mu, Chaoxu
  作者单位：Anhui Normal University; Lingnan University; Chongqing University; Tianjin University
  摘要：This article addresses theoretical limitations in Lyapunov-Krasovskii methods for time-varying delay systems through three principal contributions. First, a novel delay-dependent inequality for the derivatives of the Lyapunov function is proposed, which fundamentally distinguishes our approach from classical Halanay-type inequalities through explicit time-varying parameterization. An enhanced prescribed-time stability theorem for Filippov systems with time-varying delays and uncertainties is e...
• Safe Event-Triggered Gaussian Process Learning for Barrier-Constrained Control AI翻译
  作者：Lederer, Armin; Begzadic, Azra; Hirche, Sandra; Cortes, Jorge; Herbert, Sylvia
  作者单位：National University of Singapore; University of California System; University of California San Diego; Technical University of Munich; Technical University of Munich; Technical University of Munich
  摘要：While control barrier functions (CBFs) are employed in addressing safety, control synthesis methods based on them generally rely on accurate system dynamics. This is a critical limitation, since the dynamics of complex systems are often not fully known. Supervised machine learning techniques hold great promise for alleviating this weakness by inferring models from data. We propose a novel approach for safe event-triggered learning of Gaussian process models in CBF-based continuous-time control...
• One-Bit Consensus of Controllable Linear Multiagent Systems With Communication Noises AI翻译
  作者：An, Ru; Wang, Ying; Zhao, Yanlong; Zhang, Ji-Feng
  作者单位：Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Royal Institute of Technology; Zhongyuan University of Technology
  摘要：This article addresses the one-bit consensus of controllable linear multiagent systems (MASs) with communication noises. A consensus algorithm consisting of a communication protocol and a consensus controller is designed. The communication protocol introduces a linear compression encoding function to achieve a one-bit data rate, thereby saving communication costs. The consensus controller with a stabilization term and a consensus term is proposed to ensure the consensus of a potentially unstab...
• Data-Driven Control of Continuous-Time LTI Systems via Non-Minimal Realizations AI翻译
  作者：Bosso, Alessandro; Borghesi, Marco; Iannelli, Andrea; Notarstefano, Giuseppe; Teel, Andrew R.
  作者单位：University of Bologna; University of Stuttgart; University of California System; University of California Santa Barbara
  摘要：This article proposes an approach to design output-feedback controllers for unknown continuous-time linear time-invariant systems using only input-output data from a single experiment. To address the lack of state and derivative measurements, we introduce non-minimal realizations whose states can be observed by filtering the available data. We first apply this concept to the disturbance-free case, formulating linear matrix inequalities (LMIs) from batches of sampled signals to design a dynamic...
• Accelerated Consensus-Based SPSA Algorithm for Multisensor Multitarget Tracking Problem AI翻译
  作者：Erofeeva, Victoria; Granichin, Oleg; Sergeenko, Anna
  作者单位：Saint Petersburg State University
  摘要：Real-time control of sensor networks under communication constraints has broad applications, including target tracking and mobile robotics. Traditional centralized methods face congestion and delay issues as system size grows, motivating a shift toward decentralized multiagent approaches. This article studies a nonstationary mean-risk optimization model for distributed sensor networks with distance-only noisy measurements and unknown-but-bounded disturbances. An accelerated consensus-based sim...
• Feedback Stabilization of Polynomial Systems: From Model-Based to Data-Driven Methods AI翻译
  作者：Huang, Huayuan; Camlibel, M. Kanat; Carloni, Raffaella; van Waarde, Henk J.
  作者单位：University of Groningen
  摘要：In this study, we propose new global stabilization approaches for a class of polynomial systems in both model-based and data-driven settings. The existing model-based approach guarantees global asymptotic stability of the closed-loop system only when the Lyapunov function is radially unbounded, which limits its applicability. To overcome this limitation, we develop a new global stabilization approach that allows a broader class of Lyapunov function candidates. Furthermore, we extend this appro...
• Data-Driven Cooperative Output Regulation via Output Feedback Control AI翻译
  作者：Li, Yifei; Liu, Wenjie; Wang, Gang; Xie, Lihua; Sun, Jian; Chen, Jie
  作者单位：Beijing Institute of Technology; Nanyang Technological University; Harbin Institute of Technology
  摘要：The cooperative output regulation problem for multiagent systems (MASs) serves as a foundational framework for various cooperative control tasks. While extensively studied in model-based settings, its data-driven counterpart under output feedback remains largely unexplored. This article addresses this gap by developing a distributed data-driven output feedback control scheme grounded in the internal model principle. We first derive a representation of the original MAS using historical input-ou...
• Set-Based State Estimation For Discrete-Time Semi-Markov Jump Linear Systems Using Zonotopes AI翻译
  作者：Guan, Chaoxu; Li, You; Fei, Zhongyang; Zhao, Xudong; Zong, Guangdeng
  作者单位：Jiaxing University; Dalian University of Technology; Dalian University of Technology; Tiangong University; Weifang University
  摘要：This article is dedicated to the set-based state estimation problem of discrete-time semi-Markov jump linear systems via using zonotopes. By performing a consistency test regarding the system plant and measurement outputs, an intersected zonotope is established on the basis of a correction matrix. With the discrete-time semi-Markov kernel and P-radius concepts, the boundedness and L-infinity performance analysis are addressed for the underlying systems under the influence of unknown-but-bounde...
• High-Probability Convergence Theory for Distributed Composite Optimization With Sub-Weibull Noises AI翻译
  作者：Yu, Zhan; Shi, Zhongjie; Yuan, Deming
  作者单位：Hong Kong Baptist University; University System of Georgia; Georgia Institute of Technology; Nanjing University of Science & Technology
  摘要：With the rapid development of distributed optimization (DO) theory, distributed stochastic gradient methods (DSGMs) occupy an important position. Although the theory of different DSGMs has been widely established, the mainstream results of existing work are still derived under the condition of light-tailed stochastic gradient noises. Increasing examples from various fields indicate that the light-tailed noise model is overly idealized in many practical instances, failing to capture the complex...