2026

最新文章

• A Linear Differential Inclusion for Contraction Analysis to Known Trajectories AI翻译
  作者：Harapanahalli, Akash; Coogan, Samuel
  作者单位：University System of Georgia; Georgia Institute of Technology
  摘要：Infinitesimal contraction analysis provides exponential convergence rates between arbitrary pairs of trajectories of a system by studying the system's linearization. An essentially equivalent viewpoint arises through stability analysis of a linear differential inclusion (LDI) encompassing the incremental behavior of the system. In this note, we use contraction tools to study the exponential stability of a system to a particular known trajectory, deriving a new LDI characterizing the error betw...
• Sampling-Based Stochastic Data-Driven Predictive Control Under Data Uncertainty AI翻译
  作者：Teutsch, Johannes; Kerz, Sebastian; Wollherr, Dirk; Leibold, Marion
  作者单位：Technical University of Munich
  摘要：We present a stochastic constrained output-feedback data-driven predictive control scheme for linear time-invariant systems subject to bounded additive disturbances. The approach uses data-driven predictors based on an extension of Willems' fundamental lemma and requires only a single PE input-output data trajectory. Compared to current state-of-the-art approaches, we do not rely on availability of exact disturbance data. Instead, we leverage a novel parameterization of the unknown disturbance...
• Invariant and Attracting Sets of Stochastic Partial Functional Differential Systems AI翻译
  作者：Xu, Liguang; Li, Dingshi
  作者单位：University of Shanghai for Science & Technology; Southwest Jiaotong University
  摘要：This article is dedicated to analyzing invariant and attracting sets of stochastic partial functional differential systems. By introducing an approximate system with strong solutions and employing a limit argument along with a proof by reductio ad absurdum, several new sufficient conditions for the existence of invariant and attracting sets of the mild solutions are established. Finally, examples are provided alongside comparisons to existing results to demonstrate the superiority of our obtai...
• Analysis of Higher Order Lotka-Volterra Models: Application of S-Tensors and the Polynomial Complementarity Problem AI翻译
  作者：Cui, Shaoxuan; Zhao, Qi; Zhang, Guofeng; Jardon-Kojakhmetov, Hildeberto; Cao, Ming
  作者单位：University of Groningen; Qingdao University of Science & Technology; Hong Kong Polytechnic University; University of Groningen
  摘要：It is known that the effect of species' density on its growth is nonadditive in real ecological systems. This challenges the conventional Lotka-Volterra model, where the interactions are always pairwise and their effects are additive. To address this challenge, we introduce higher order interactions, which are able to capture, for example, the indirect effect of one species on a second one correlating to yet a third. Towards this end, we study a general higher order Lotka-Volterra model. We pr...
• Unobservable Systems: No Problem for Noise Identification AI翻译
  作者：Kost, Oliver; Dunik, Jindrich; Puncochar, Ivo; Straka, Ondrej
  作者单位：University of West Bohemia Pilsen
  摘要：This article deals with the noise identification of a linear time-varying stochastic dynamic system described by the state-space model. In particular, the stress is laid on the design of the correlation measurement difference method for estimation of the state and measurement noise covariance matrices for both observable and unobservable systems with possibly unknown input sequence. The method provides unbiased and consistent estimates and is implemented in a publicly available Matlab toolbox ...
• Backward Reachability Analysis of Perturbed Continuous-Time Linear Systems Using Set Propagation AI翻译
  作者：Wetzlinger, Mark; Althoff, Matthias
  作者单位：Technical University of Munich
  摘要：Backward reachability analysis computes the set of states that reach a target set under the competing influence of control inputs and disturbances. Depending on their interplay, the backward reachable set either represents all states that can be steered into the target set or all states that cannot avoid entering it-the corresponding solutions can be used for controller synthesis and safety verification, respectively. A popular technique for backward reachable set computation solves Hamilton-J...
• Asymptotical Fault-Tolerant Time-Varying Tracking Control of Networked Mobile Flexible Manipulators Under Prescribed Performances and DoS Attacks AI翻译
  作者：Yao, Xiangqian; Li, Xing; Liu, Zhijie; Gao, Huanli; Li, Jianqiang; Liu, Yu
  作者单位：South China University of Technology; Northeastern University - China; Northeastern University - China; University of Science & Technology Beijing; South China University of Technology; Shenzhen University
  摘要：This article focuses on the asymptotic time-varying consensus tracking for the mobile dual flexible manipulators with unknown gain faults, prescribed performances, and denial-of-service attacks. Our main contribution is to provide a novel distributed boundary control scheme for reaching the asymptotic consensus tracking of partial differential equation coupled ordinary differential equation systems under a heterogeneous linear leader. To this end, an adaptive distributed switched observer is f...
• Communication and Control Co-Design in Noncooperative Games AI翻译
  作者：Aggarwal, Shubham; Basar, Tamer; Maity, Dipankar
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of North Carolina; University of North Carolina Charlotte
  摘要：In this article, we revisit a communication-control co-design problem for a class of two-player stochastic differential games on an infinite horizon. Each player represents two active decision makers, namely, a scheduler and a remote controller, which cooperate to optimize over a global objective while competing with the other player. Each player's scheduler can only intermittently relay state information to its respective controller due to associated cost/constraint to communication. The sche...
• Robust Moving Horizon Estimation With Diverse Prior Predictions for Nonlinear Systems AI翻译
  作者：Arezki, H.; Zemouche, A.; Alessandri, A.
  作者单位：University of Genoa; Universite de Lorraine; Universite de Lorraine; Centre National de la Recherche Scientifique (CNRS)
  摘要：This article addresses robust stability analysis for moving horizon estimation (MHE) in nonlinear systems and proposes new conditions for tuning the MHE cost function parameters. These conditions are directly linked to the MHE window size and the incremental exponential input/output-to-state stability (i-EIOSS) coefficients of the system. Our approach begins by introducing a general constraint equation within the MHE optimization program, combined with a filtering prior prediction technique. T...
• Differentially Private Gradient-Tracking-Based Distributed Stochastic Optimization Over Directed Graphs AI翻译
  作者：Chen, Jialong; Wang, Jimin; 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; University of Science & Technology Beijing; Zhongyuan University of Technology
  摘要：This article proposes a differentially private gradient-tracking-based distributed stochastic optimization algorithm over directed graphs. In particular, privacy noises are incorporated into each agent's state and tracking variable to mitigate information leakage, after which the perturbed states and tracking variables are transmitted to neighbors. We design two novel schemes for the step-sizes and the sampling number within the algorithm. The sampling parameter-controlled subsampling method e...