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最新文章

• Output Regulation of Linear Stochastic Systems With Unstable Linear Exogenous Systems AI翻译
  作者：Ma, Ji; Yu, Xiao; Lan, Weiyao; Chen, Zhiyong
  作者单位：Xiamen University; Xiamen University; University of Newcastle
  摘要：This article investigates the output regulation problem of multi-input-multi-output (MIMO) linear stochastic systems and unstable linear exogenous systems. First, stochastic output regulator equations are constructed to characterize the solvability of the output regulation problem. Then, a necessary and sufficient condition on the solvability of the output regulator equation is established. Under this condition, not only the relationship between the output regulation of linear stochastic syste...
• Fully Distributed Event-Triggered Control of Nonlinear Multiagent Systems Under Directed Graphs: A Model-Free DRL Approach AI翻译
  作者：Shi, Xiongtao; Li, Yanjie; Du, Chenglong; Shi, Yang; Yang, Chunhua; Gui, Weihua
  作者单位：Harbin Institute of Technology; Harbin Institute of Technology; Central South University; University of Victoria
  摘要：This article addresses the consensus problem of a class of unknown nonlinear multiagent systems (MASs) under directed graphs via a novel model-free deep reinforcement learning (DRL) based fully distributed event-triggered control (ETC) method. First, the DRL-based feedback linearization approach is developed to learn an approximated linearized control protocol in a model-free manner. Then, a novel adaptive event-triggered mechanism is proposed to save more communication resources and reduce th...
• Data-Based System Representations From Irregularly Measured Data AI翻译
  作者：Alsalti, Mohammad; Markovsky, Ivan; Lopez, Victor G.; Mueller, Matthias A.
  作者单位：Leibniz University Hannover; Universitat Politecnica de Catalunya; Centre Internacional de Metodes Numerics en Enginyeria (CIMNE); ICREA
  摘要：Nonparametric representations of dynamical systems based on the image of a Hankel matrix of data are extensively used for data-driven control. However, if samples of data are missing, obtaining such representations becomes a difficult task. By exploiting the kernel structure of Hankel matrices of irregularly measured data generated by a linear time-invariant system, we provide computational methods for which any complete finite-length behavior of the system can be obtained. For the special cas...
• Convergence Theorems for Stochastic Impulsive Systems With Application to Discrete-Time Stochastic Feedback Control AI翻译
  作者：Luo, Shixian; Deng, Feiqi; Jiang, Yan
  作者单位：Guangxi University; South China University of Technology
  摘要：This article is devoted to stochastic convergence theorems for stochastic impulsive systems (SISs) and their application to discrete-time stochastic feedback control (DTSFC). A general stochastic Barb & abreve;lat's lemma, which only requires that the concerned stochastic processes are almost surely integrable rather than absolutely integrable in the sense of expectation, for piecewise continuous adapted processes is first proposed, which is truly parallel to the deterministic one. As an exten...
• Output Regulation of Linear Stochastic Systems With Unstable Linear Exogenous Systems AI翻译
  作者：Ma, Ji; Yu, Xiao; Lan, Weiyao; Chen, Zhiyong
  作者单位：Xiamen University; Xiamen University; University of Newcastle
  摘要：This article investigates the output regulation problem of multi-input-multi-output (MIMO) linear stochastic systems and unstable linear exogenous systems. First, stochastic output regulator equations are constructed to characterize the solvability of the output regulation problem. Then, a necessary and sufficient condition on the solvability of the output regulator equation is established. Under this condition, not only the relationship between the output regulation of linear stochastic syste...
• Fully Distributed Event-Triggered Control of Nonlinear Multiagent Systems Under Directed Graphs: A Model-Free DRL Approach AI翻译
  作者：Shi, Xiongtao; Li, Yanjie; Du, Chenglong; Shi, Yang; Yang, Chunhua; Gui, Weihua
  作者单位：Harbin Institute of Technology; Harbin Institute of Technology; Central South University; University of Victoria
  摘要：This article addresses the consensus problem of a class of unknown nonlinear multiagent systems (MASs) under directed graphs via a novel model-free deep reinforcement learning (DRL) based fully distributed event-triggered control (ETC) method. First, the DRL-based feedback linearization approach is developed to learn an approximated linearized control protocol in a model-free manner. Then, a novel adaptive event-triggered mechanism is proposed to save more communication resources and reduce th...
• Optimal Control of Logically Constrained Partially Observable and Multiagent Markov Decision Processes AI翻译
  作者：Kalagarla, Krishna C.; Kartik, Dhruva; Shen, Dongming; Jain, Rahul; Nayyar, Ashutosh; Nuzzo, Pierluigi
  作者单位：University of Southern California; University of New Mexico; Amazon.com; Massachusetts Institute of Technology (MIT)
  摘要：Autonomous systems often have logical constraints arising, for example, from safety, operational, or regulatory requirements. Such constraints can be expressed using temporal logic specifications. The system state is often partially observable. Moreover, it could encompass a team of multiple agents with a common objective but disparate information structures and constraints. In this article, we first introduce an optimal control theory for partially observable Markov decision processes with fi...
• Learning-Based Sparse Sensing With Performance Guarantees AI翻译
  作者：Vafaee, Reza; Siami, Milad
  作者单位：Northeastern University
  摘要：In this study, we address the challenge of sensor scheduling in discrete-time linear dynamical networks. We propose a novel learning-based rounding method aimed at converting a provided weighted sensor schedule into a sparse, unweighted schedule while preserving a comparable level of observability performance to the original weighted schedule. We introduce the notion of L-systemic performance measures, which enjoy characteristics such as homogeneity, monotonicity, convexity, and Lipschitz cont...
• Sequential Learning and Control: Targeted Exploration for Robust Performance AI翻译
  作者：Venkatasubramanian, Janani; Koehler, Johannes; Berberich, Julian; Allgoewer, Frank
  作者单位：University of Stuttgart; Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：In this article, we present a novel dual control strategy for uncertain linear systems based on targeted harmonic exploration and gain-scheduling with performance and excitation guarantees. In the proposed sequential approach, robust control is implemented after exploration with the main feature that the exploration is optimized with respect to the robust control performance. Specifically, we leverage recent results on finite excitation using spectral lines to determine a high-probability lowe...
• Input-Output Stochastic Stability for Markov Jump Linear Systems AI翻译
  作者：Costa, Eduardo F.
  作者单位：Universidade de Sao Paulo
  摘要：Among several stability notions for dynamical systems, input-output stability is significant in applications where one is interested in the input-output relation rather than in the internal dynamics. This article addresses a notion of input-output stability for Markov jump linear systems and presents a testable, necessary and sufficient condition. Examples show that this stability notion is weaker than stochastic stability (a usual notion of stability for the considered class of systems), and ...