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作者：Ma, Yong-Sheng; Sun, Jian; Xu, Yong; Cui, Shi-Sheng; Wu, Zheng-Guang
作者单位：Beijing Institute of Technology; Zhejiang University
摘要：In this article, we investigate the optimal control problem for an unknown linear time-invariant system. To solve this problem, a novel composite policy iteration algorithm based on adaptive dynamic programming is developed to adaptively learn the optimal control policy from system data. The existing methods require the initial stabilizing control policy, the persistence of excitation (PE) condition and the data storage to ensure the algorithm convergence. Fundamentally different from them, th...
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作者：Sebastian, Eduardo; Aldana-Lopez, Rodrigo; Aragues, Rosario; Montijano, Eduardo; Sagues, Carlos
作者单位：University of Zaragoza; University of Zaragoza
摘要：This article presents the first discrete-time distributed algorithm to track the tightest ellipsoids that outer approximates the global dynamic intersection of ellipsoids. Given an undirected network, we consider a setup where each node measures an ellipsoid, defined as a time-varying positive semidefinite matrix. The goal is to devise a distributed algorithm to track the tightest outer approximation of the intersection of all the ellipsoids. The solution is based on a novel distributed reform...
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作者：Xin, Lei; Ye, Lintao; Chiu, George; Sundaram, Shreyas
作者单位：Purdue University System; Purdue University; Chinese University of Hong Kong; Huazhong University of Science & Technology; Purdue University System; Purdue University; Purdue University in Indianapolis; Purdue University System; Purdue University
摘要：We consider the problem of learning the dynamics of a linear system when one has access to data generated by an auxiliary system that shares similar (but not identical) dynamics, in addition to data from the true system. We use a weighted least squares approach, and provide a finite sample error bound of the learned model as a function of the number of samples and various system parameters from the two systems as well as the weight assigned to the auxiliary data. We show that the auxiliary dat...
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作者：Huang, Pengyan; Wang, Guangchen; Wang, Shujun
作者单位：Shandong University; Shandong University of Finance & Economics; Shandong University
摘要：In this article, we focus on a type of linear-quadratic (LQ) mean-field game of stochastic differential equations with a terminal state constraint and common noise, where a coupling structure enters the state equation, cost functional, and constraint condition. First, by virtue of the mean-field method, we introduce an auxiliary problem of the original game, which is a constrained optimal control problem. Second, by virtue of the Lagrangian multiplier method and stochastic maximum principle, a...
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作者：Lan, Hua; Zhao, Shijie; Hu, Jinjie; Wang, Zengfu; Fu, Jing
作者单位：Northwestern Polytechnical University; Royal Melbourne Institute of Technology (RMIT)
摘要：This article addresses state estimation problems with unknown process and measurement noise covariances in both linear and nonlinear systems. By formulating the joint estimation of system state and noise parameters into an optimization problem, a novel adaptive Kalman filter method based on conjugate-computation variational inference, referred to as CVIAKF, is proposed to approximate the joint posterior probability density function of the latent variables. Unlike existing adaptive Kalman filte...
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作者：Li, Yushan; He, Jianping; Chen, Cailian; Guan, Xinping; Cai, Lin
作者单位：Shanghai Jiao Tong University; University of Victoria
摘要：The security of mobile robotic networks (MRNs) has been an active research topic in recent years. This article aims to secure the ubiquitous formation control of MRNs against the replacement attack, where an external robot can replace a formation robot by compromising the communication and physically interfering with the victim simultaneously. To counter this advanced attack, the novel idea of this work is to leverage the physical proximity of the formation shape and the interaction topology a...
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作者：Abdelgalil, Mahmoud; Poveda, Jorge I.
作者单位：University of California System; University of California San Diego
摘要：The stability of dynamical systems with oscillatory behaviors and well-defined average vector fields has traditionally been studied using averaging theory. These tools have also been applied to hybrid dynamical systems, which combine continuous and discrete dynamics. However, most averaging results for hybrid systems are limited to first-order methods, hindering their use in systems and algorithms that require high-order averaging techniques, such as hybrid Lie-bracket-based extremum-seeking a...
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作者：Friedrich, Folke; Fokken, Nils; Noack, Matti; Reger, Johann
作者单位：Technische Universitat Ilmenau
摘要：In this article, the state estimation of distributed parameter systems using the modulating function method is extended to systems of two or higher spatial dimensions with spatially varying coefficients and general boundary conditions. At the center of the state observer approach lies the construction and solvability analysis of systematically obtained kernel equations determining the modulating functions. In addition, a method for the state estimation of a class of parabolic systems with time...
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作者：Pachal, Soumen; Bhatnagar, Shalabh; Prashanth, L. A.
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Madras; Indian Institute of Science (IISC) - Bangalore; Indian Institute of Science (IISC) - Bangalore; Bosch; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Madras
摘要：We present a family of generalized simultaneous perturbation-based gradient search (GSPGS) estimators that use noisy function measurements. The number of function measurements required by each estimator is guided by the desired level of accuracy. We first present in detail unbalanced generalized simultaneous perturbation stochastic approximation estimators and later present the balanced versions of these. We extend this idea further and present the generalized smoothed functional and generaliz...
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作者：Jacquet, Quentin; van Ackooij, Wim; Alasseur, Clemence; Gaubert, Stephane
作者单位：Electricite de France (EDF); Institut Polytechnique de Paris; Ecole Polytechnique; Inria; Centre National de la Recherche Scientifique (CNRS)
摘要：We consider a control problem for a heterogeneous population composed of agents able to switch at any time between different options. The controller aims to maximize an average gain per time unit, supposing that the population is of infinite size. This leads to an ergodic control problem for a mean-field Markov decision process in which the state space is a product of simplices, and the population evolves according to controlled linear dynamics. By exploiting contraction properties of the dyna...
