5期

最新文章

• Aggregated Bisimulation and Identification of Finite-Valued Networks AI翻译
  作者：Ji, Zhengping; Zhang, Xiao; Cheng, Daizhan
  作者单位：Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Hong Kong Polytechnic University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
  摘要：We propose a method that combines aggregation and bisimulation to approximate large finite-valued networks by smaller models. With the algebraic state-space representation of a quotient system under observational equivalence, the aggregated bisimulation is performed by partitioning a network into blocks and replacing the dynamics of each block by that of its quotient system. If the aggregation is not a bisimulation, these quotient systems can be further replaced by probabilistic networks based...
• IRKA Is a Riemannian Gradient Descent Method AI翻译
  作者：Mlinaric, Petar; Beattie, Christopher A.; Drmac, Zlatko; Gugercin, Serkan
  作者单位：Virginia Polytechnic Institute & State University; University of Zagreb; Virginia Polytechnic Institute & State University; Virginia Polytechnic Institute & State University
  摘要：The iterative rational Krylov algorithm (IRKA) is a commonly used fixed point iteration developed to minimize the H-2 model order reduction error. In this work, the IRKA is recast as a Riemannian gradient descent method with a fixed step size over the manifold of rational functions having fixed degree. This interpretation motivates the development of a Riemannian gradient descent method utilizing as a natural extension variable step size and line search. Comparisons made between the IRKA and t...
• Estimating True Beliefs in Opinion Dynamics With Social Pressure AI翻译
  作者：Tang, Jennifer; Adler, Aviv; Ajorlou, Amir; Jadbabaie, Ali
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Analog Devices, Inc.
  摘要：Social networks often exert social pressure, causing individuals to adapt their expressed opinions to conform to their peers. An agent in such systems can be modeled as having an (true and unchanging) inherent belief while broadcasting a declared opinion at each time step based on his/her inherent belief and the past declared opinions of his/her neighbors. An important question in this setting is parameter estimation: how to disentangle the effects of social pressure to estimate inherent belie...
• Iterative Nonconvex Distributed MPC With Flexible Termination Strategy AI翻译
  作者：Wu, Jinxian; Dai, Li; Xia, Yuanqing
  作者单位：Beijing Institute of Technology
  摘要：This article proposes an iterative distributed model predictive control (DMPC) algorithm for multiple dynamically decoupling linear systems subject to both local state and input constraints, as well as coupling constraints that may be nonconvex (e.g., collision avoidance constraints). This issue has not been extensively explored, particularly in the context of allowing flexible termination of inner optimization problem calculations in accordance with the sample time. In this article, we presen...
• Orthogonal Projection-Based Fault Detection for Linear Discrete-Time Varying Systems AI翻译
  作者：Li, Linlin; Ding, Steven X.; Zhong, Maiying; Peng, Kaixiang
  作者单位：University of Science & Technology Beijing; University of Duisburg Essen; Shandong University of Science & Technology
  摘要：This article is devoted to one-class fault detection in linear discrete-time varying (LDTV) systems with uncertainties. Specifically, following the Hilbert Projection theorem, the residual generation problem is solved by means of an orthogonal projection of process data onto system subspaces in Hilbert space. The resulted Pythagorean equation enables establishing an adaptive threshold driven by the residual signal and using gap metric as the similarity measure. In this projection-based fault d...
• Deterministic Learning-Based Tracking Control for Parabolic PDE Systems With Infinite-Dimensional Nonlinear Uncertain Dynamics AI翻译
  作者：Zhang, Jingting; Yuan, Chengzhi; Wu, Fen; Wang, Cong; Cheng, Hong
  作者单位：University of Electronic Science & Technology of China; University of Rhode Island; North Carolina State University; Shandong University
  摘要：In this article, we investigate the joint problem of dynamics learning and tracking control for a class of parabolic partial differential equation (PDE) systems with infinite-dimensional uncertain nonlinear dynamics. A new learning control scheme is proposed based on the deterministic learning (DL) theory. One key feature of the proposed scheme is its capability of accurately learning the system's nonlinear uncertain dynamics during real-time tracking control with provable stability and conver...
• Sample-Efficient Reinforcement Learning With Temporal Logic Objectives: Leveraging the Task Specification to Guide Exploration AI翻译
  作者：Kantaros, Yiannis; Wang, Jun
  作者单位：Washington University (WUSTL)
  摘要：In this article, we address the problem of learning optimal control policies for systems with uncertain dynamics and high-level control objectives specified as linear temporal logic (LTL) formulas. Uncertainty is considered in the workspace structure and the outcomes of control decisions giving rise to an unknown Markov decision process (MDP). Existing reinforcement learning (RL) algorithms for LTL tasks typically rely on exploring a product MDP state-space uniformly (using e.g., an $\epsilon$...
• Minimum Initial Marking Estimation in Labeled Petri Nets Using Minimum Token Number Prediction AI翻译
  作者：Yue, Hao; Xu, Yakun; Hu, Hesuan; Wu, Weimin; Li, Lingxi
  作者单位：China University of Petroleum; Nanyang Technological University; Xidian University; Zhejiang University; Zhejiang University; Purdue University System; Purdue University; Purdue University in Indianapolis
  摘要：This article proposes an approach to addressing the problem of minimum initial marking (MuIM) estimation for labeled Petri nets (LPNs). We introduce the important concept of a label synthesis net for LPNs and develop a method for predicting the minimum number of tokens. By using this prediction method, we develop an algorithm that has polynomial complexity in the length of the observed label sequence for estimating MuIMs. An illustrative example is provided to show the effectiveness and effici...
• Dynamic Regret for Distributed Online Composite Optimization AI翻译
  作者：Hou, Ruijie; Yu, Yang; Li, Xiuxian
  作者单位：Tongji University; Tongji University; Tongji University
  摘要：This article focuses on online composite optimization over multiagent networks. In the distributed setting, each agent has its own local loss function, which consists of a convex, strongly convex or strongly convex and smooth function, and a time-varying nonsmooth regularizer. Two distributed online algorithms are proposed and corresponding dynamic regrets are analyzed. Two proposed algorithms are based on signs of relative states. The first algorithm obtains O(root T(C-T + 1)) dynamic regret ...
• Noncollocated Output Feedback Control for the Semilinear Parabolic PDEs Under Input and Output Quantization AI翻译
  作者：Zhao, Xuena; Liu, Zhijie; Zhang, Shuang; Liu, Yu; He, Wei
  作者单位：University of Science & Technology Beijing; University of Science & Technology Beijing; South China University of Technology; South China University of Technology
  摘要：In the context of increasingly networked control systems, this article concentrates on the noncollocated control issue of input and output quantization for industrial processes governed by semilinear parabolic partial differential equation (PDE) systems. Both the control and measurement signals are quantized and transmitted through the network, which causes signal errors and reduces the stability and robustness of the system. A Luenberger-type PDE observer is developed to overcome the control ...