2023

最新文章

• Synchronous Networks Over Finite Fields AI翻译
  作者：Wang, Jin; Feng, Jun-e; Yu, Yongyuan; Huang, Hua-Lin
  作者单位：Shandong University; Huaqiao University
  摘要：This article investigates the synchronization problem of networks over finite fields. First, based on the finite-field synchronizable property of matrices, a necessary and sufficient condition is derived for finite-field synchronous networks. Then, the inverse recursion subspaces of networks over finite fields are studied. It is revealed that the synchronization of finite-field networks can be determined by a fraction of states. Finally, as an application, the obtained results are generalized ...
• The Stochastic Robustness of Nominal and Stochastic Model Predictive Control AI翻译
  作者：Mcallister, Robert D.; Rawlings, James B.
  作者单位：University of California System; University of California Santa Barbara
  摘要：In this work, we establish and compare the stochastic and deterministic robustness properties achieved by nominal model predictive control (MPC), stochastic MPC (SMPC), and a proposed constraint tightened MPC (CMPC) formulation, which represents an idealized version of tube-based MPC. We consider three definitions of robustness for nonlinear systems and bounded disturbances: robustly asymptotically stable (RAS), robustly asymptotically stable in expectation (RASiE), and RASiE with respect to t...
• Stability Analysis of Time-Varying Neutral Stochastic Hybrid Delay System AI翻译
  作者：Chen, Huabin; Shi, Peng; Lim, Cheng-Chew
  作者单位：Nanchang University; University of Adelaide
  摘要：This note analyzes the stochastic stability for time varying neutral stochastic hybrid delay system, which includes the stability in pth(p = 2)-moment, the asymptotical stability in pth(p= 2)-moment, the exponential stability in pth(p = 2) moment, and the almost surely exponential stability. One modified version of generalized delay integral inequality, the Lyapunov- Krasovskii function, and the stochastic analysis are used. The proposed methodology can surmount the analytical difficulty, whic...
• The Implicit Maximal Positively Invariant Set AI翻译
  作者：Rakovic, Sasa V.; Zhang, Sixing
  作者单位：Beijing Institute of Technology; Beijing Institute of Technology
  摘要：This article introduces an alternative characterization, together with indirect computation and implicit representation, of the maximal positively invariant set for the nonlinear dynamics and closed constraints. The introduced alternative characterization, indirect computation, and implicit representation of the maximal positively invariant set are novel features that, when combined together, overcome successfully dimensionality related limitations of the standard explicit computation of the m...
• Stochastic Event-Triggered Variational Bayesian Filtering AI翻译
  作者：Lv, Xiaoxu; Duan, Peihu; Duan, Zhisheng; Chen, Guanrong; Shi, Ling
  作者单位：Peking University; City University of Hong Kong; Hong Kong University of Science & Technology
  摘要：This article proposes an event-triggered variational Bayesian filter for remote state estimation with unknown and time-varying noise covariances. After presetting multiple nominal process noise covariances and an initial measurement noise covariance, a variational Bayesian method and a fixed-point iteration method are utilized to jointly estimate the posterior state vector and the unknown noise covariances under a stochastic event-triggered mechanism. The proposed algorithm ensures low communi...
• Adaptive Tracking Control With Global Performance for Output-Constrained MIMO Nonlinear Systems AI翻译
  作者：Kong, Linghuan; He, Wei; Liu, Zhijie; Yu, Xinbo; Silvestre, Carlos
  作者单位：University of Science & Technology Beijing; University of Science & Technology Beijing; University of Science & Technology Beijing; University of Macau; Universidade de Lisboa
  摘要：In this article, a novel adaptive tracking control technique is developed for multiple-input-multiple-output nonlinear systems with model uncertainty and under output constraints occurring in a limited time interval (OCOLT). The OCOLT, which is a type of constraints occurring sometime after (rather than the beginning of) system operation and with limited duration, can be found in many practical systems and has not been effectively addressed in the literature until now. By designing a new shift...
• Smoother Entropy for Active State Trajectory Estimation and Obfuscation in POMDPs AI翻译
  作者：Molloy, Timothy L.; Nair, Girish N.
  作者单位：University of Melbourne; Australian National University; University of Melbourne
  摘要：In this article, we study the problem of controlling a partially observed Markov decision process (POMDP) to either aid or hinder the estimation of its state trajectory. We encode the estimation objectives via the smoother entropy, which is the conditional entropy of the state trajectory given measurements and controls. Consideration of the smoother entropy contrasts with previous approaches that instead resort to marginal (or instantaneous) state entropies due to tractability concerns. By est...
• Reactive Symbolic Planning and Control in Dynamic Adversarial Environments AI翻译
  作者：Shamgah, Laya; Tadewos, Tadewos G.; Newaz, Abdullah Al Redwan; Karimoddini, Ali; Esterline, Albert C.
  作者单位：University of North Carolina; North Carolina A&T State University; University of North Carolina; North Carolina A&T State University; University of Louisiana System; University of New Orleans
  摘要：Satisfying both safety and reachability requirements in dynamic adversarial environments is very challenging, particularly when little or no information about the dynamics and intentions of the adversarial objects is available. Therefore, this article addresses the problem of path planning and control of autonomous vehicles in a dynamic adversarial reach-avoid scenario with two noncooperative vehicles and their competitive objectives: 1) reaching a target and avoiding the other vehicle for one...
• Robust Uncertainty Bounds in Reproducing Kernel Hilbert Spaces: A Convex Optimization Approach AI翻译
  作者：Scharnhorst, Paul; Maddalena, Emilio T.; Jiang, Yuning; Jones, Colin N.
  作者单位：Swiss Center for Electronics & Microtechnology (CSEM); Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
  摘要：The problem of establishing out-of-sample bounds for the values of an unknown ground-truth function is considered. Kernels and their associated Hilbert spaces are the main formalism employed herein, along with an observational model where outputs are corrupted by bounded measurement noise. The noise can originate from any compactly supported distribution, and no independent assumptions are made on the available data. In this setting, we show how computing tight, finite-sample uncertainty bound...
• Resource-Aware Discretization of Accelerated Optimization Flows: The Heavy-Ball Dynamics Case AI翻译
  作者：Vaquero, Miguel; Mestres, Pol; Cortes, Jorge
  作者单位：IE University; University of California System; University of California San Diego
  摘要：This article proposes a methodology for discretizing accelerated optimization flows while retaining their convergence properties. Inspired by the success of resource-aware control in developing efficient closed-loop feedback implementations on digital systems, we view the last sampled state of the system as the resource to be aware of. We illustrate our design methodology for discretization on a newly introduced continuous-time dynamics, the heavy-ball dynamics with displaced gradient. Our alg...