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作者：Braun, Sarah; Albrecht, Sebastian; Lucia, Sergio
作者单位：Dortmund University of Technology
摘要：Adversarial attacks on controllers of dynamic systems have become a serious threat to many real-world systems, making methods for fast identification of attacks an indispensable part of autonomous systems. With the increasing use of model-based controllers, it is valid to exploit model knowledge also for attack identification as long as privacy of individual components is maintained. A scalable, model-based method to reveal generic attacks was introduced in our previous work and is further inv...
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作者：Feiling, Jan; Belabbas, Mohamed-Ali; Ebenbauer, Christian
作者单位：University of Stuttgart; University of Illinois System; University of Illinois Urbana-Champaign; RWTH Aachen University
摘要：In this article, multivariable derivative-free optimization algorithms for unconstrained optimization problems are developed. A novel procedure for approximating the gradient of multivariable objective functions based on noncommutative maps is introduced. The procedure is based on the construction of an exploration sequence to specify where the objective function is evaluated and the definition of so-called gradient generating functions which are composed with the objective function, such that...
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作者：Giaccagli, Mattia; Astolfi, Daniele; Andrieu, Vincent; Marconi, Lorenzo
作者单位：Centre National de la Recherche Scientifique (CNRS); Universite Claude Bernard Lyon 1; University of Bologna
摘要：In this article, we study the problem of constant output regulation for a class of input-affine multi-input multi-output nonlinear systems, which do not necessarily admit a normal form. We allow the references and the disturbances to be arbitrarily large and the initial conditions of the system to range in the full-state space. We cast the problem in the contraction framework, and we rely on the common approach of extending the system with an integral action processing the regulation error. We...
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作者：Talebi, Shahriar; Alemzadeh, Siavash; Rahimi, Niyousha; Mesbahi, Mehran
作者单位：University of Washington; University of Washington Seattle
摘要：Learning, say through direct policy updates, often requires assumptions such as knowing a priori that the initial policy (gain) is stabilizing, or persistently exciting (PE) input-output data, is available. In this article, we examine online regulation of (possibly unstable) partially unknown linear systems with no prior access to an initial stabilizing controller nor PE input-output data; we instead leverage the knowledge of the input matrix for online regulation. First, we introduce and char...
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作者：Zhu, Jin; Xia, Kai; Ling, Qiang; Chen, Wei; Dullerud, Geir E.
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; University of Illinois System; University of Illinois Urbana-Champaign
摘要：This article is devoted to a specific kind of discrete-time switched linear systems, where the switching signal is governed by a Markov chain, i.e., Markovian jump linear systems. For such systems, a mode feedback control mechanism is adopted to adjust the mode transition probability matrix, which is referred to as the switching law design, and the optimal mode feedback controller is sought to minimize a quadratic performance index containing both the system state and the mode feedback control...
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作者：Shao, Guangru; Wang, Rui; Ye, Maojiao; Wang, Xue-Fang
作者单位：Yantai University; Dalian University of Technology; Dalian University of Technology; Nanjing University of Science & Technology; Dalian University of Technology
摘要：This article investigates the Nash equilibrium (NE) seeking problem for games in the presence of input dead-zone nonlinearity. The purpose of each player is to minimize its own cost function, which depends not only on its own decision variable, but also on decision variables of the other players. To obtain an NE, a novel two-time-scale distributed algorithm is designed. This new strategy consists of two parts: one is the fast compensating dynamics, which can rapidly compensate the effect of in...
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作者：Kato, Rui; Cetinkaya, Ahmet; Ishii, Hideaki
作者单位：Institute of Science Tokyo; Tokyo Institute of Technology; Research Organization of Information & Systems (ROIS); National Institute of Informatics (NII) - Japan
摘要：Motivated by the recent security issues in cyber-physical systems, this article studies the stabilization problem of networked control systems under denial-of-service (DoS) attacks. In particular, we consider to stabilize a nonlinear system with limited data rate via linearization. We employ a deterministic DoS attack model constrained in terms of attacks' frequency and duration, allowing us to cover a large class of potential attacks. To achieve asymptotic stabilization, we propose a resilien...
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作者：Zhang, Wenhan; Wang, Zhenhua; Raissi, Tarek; Shen, Yi
作者单位：Harbin Institute of Technology
摘要：This article proposes an intervalestimation method for discrete-time Lipschitz nonlinear systems via observer design and ellipsoidal analysis. A robust observer with novel structure is presented, which provides more degrees of design freedom and can be applied to enhance the interval estimation performance. To handle the nonlinear term in Lipschitz systems, we use the reformulated Lipschitz property to transform the nonlinear error dynamics into a linear parameter-varying form. After the trans...
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作者：Li, Yingying; Tang, Yujie; Zhang, Runyu; Li, Na
作者单位：Harvard University
摘要：This article considers a distributed reinforcement learning problem for decentralized linear quadratic (LQ) control with partial state observations and local costs. We propose a zero-order distributed policy optimization algorithm (ZODPO) that learns linear local controllers in a distributed fashion, leveraging the ideas of policy gradient, zero-order optimization, and consensus algorithms. In ZODPO, each agent estimates the global cost by consensus, and then conducts local policy gradient in ...
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作者：Carnerero, A. D.; Ramirez, D. R.; Alamo, T.
作者单位：University of Sevilla
摘要：This work presents a new methodology to obtain probabilistic interval predictions of a dynamical system. The proposed strategy uses stored past system measurements to estimate the future evolution of the system. The method relies on the use of dissimilarity functions to estimate the conditional probability density function of the outputs. A family of empirical probability density functions, parameterized by means of two scalars, is introduced. It is shown that the proposed family encompasses t...
