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作者：Meng, Min; Li, Xiuxian; Chen, Jie
作者单位：Tongji University; Tongji University
摘要：This article studies distributed online bandit learning of generalized Nash equilibria for online games, where the cost functions of all players and coupled constraints are time-varying. The function values, rather than full information about cost and local constraint functions, are revealed to local players with time delays. The goal of each player is to selfishly minimize its own cost function with no future information, subject to a strategy set constraint and time-varying coupled inequalit...
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作者：Allibhoy, Ahmed; Cortes, Jorge
作者单位：University of California System; University of California San Diego
摘要：This article considers the problem of designing a continuous-time dynamical system that solves a constrained nonlinear optimization problem and makes the feasible set forward invariant and asymptotically stable. The invariance of the feasible set makes the dynamics anytime, when viewed as an algorithm, meaning it returns a feasible solution regardless of when it is terminated. Our approach augments the gradient flow of the objective function with inputs defined by the constraint functions, tre...
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作者：Li, Shilei; Shi, Dawei; Lou, Yunjiang; Zou, Wulin; Shi, Ling
作者单位：Hong Kong University of Science & Technology; Beijing Institute of Technology; Harbin Institute of Technology
摘要：Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, the noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ...
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作者：Rios, Hector; de Loza, Alejandra Ferreira; Efimov, Denis; Franco, Roberto
作者单位：Universite de Lille; Centre National de la Recherche Scientifique (CNRS); Inria
摘要：This article deals with the problem of time-varying parameter identification in dynamical regression models affected by disturbances. The disturbances comprise time-dependent external perturbations and nonlinear unmodeled dynamics. With this aim in mind, we propose a robust nonlinear adaptive observer. The algorithm ensures the asymptotic convergence of the parameter identification error to an acceptably small region around the origin in the presence of disturbances. The synthesis of the adapt...
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作者：Yekkehkhany, Ali; Feng, Han; Ying, Donghao; Lavaei, Javad
作者单位：University of California System; University of California Berkeley
摘要：Stochastic time-varying optimization is an integral part of learning in which the shape of the function changes over time in a nondeterministic manner. This article considers multiple models of stochastic time variation and analyzes the corresponding notion of hitting time for each model, i.e., the period after which optimizing the stochastic time-varying function reveals informative statistics on the optimization of the target function. The studied models of time variation are motivated by ad...
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作者：Hua, Chang-Chun; Li, Hao; Li, Kuo; Ning, Pengju
作者单位：Yanshan University; Hebei University of Science & Technology; University of Duisburg Essen
摘要：This article studies the adaptive prescribed-time control problem for a class of nonlinear systems with unknown time-varying control coefficients. Existing methods for unknown control direction problems can only achieve asymptotic stability based on Barbalat's lemma. Different from these results, we present a new theorem in conjunction with Nussbaum functions to achieve the prescribed-time stability. Meanwhile, the conservative condition of Nussbaum parameters is relaxed under time-varying con...
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作者：Wang, Weizhe; Fu, Yue; Fu, Jun
作者单位：Northeastern University - China
摘要：In this article, for continuous-time nonlinear systems with unknown dynamics and multiple equilibrium points, an indirect adaptive optimal tracking switching controller consisting of multiple linear indirect adaptive optimal tracking controllers, a robust compensator, and an optimal switching mechanism is proposed by combining optimal tracking scheme with embedding-transformation technique and adaptive algorithm. First, multiple linearized models are used to establish a controller design model...
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作者：Zhao, Xueyan; Deng, Feiqi
作者单位：South China University of Technology
摘要：In this article, stabilization of systems by delayed noisy states is investigated. The time delays in the stabilizing noisy states are extended into the general form. To support this novelty, the familiar Doob martingale inequality in the continuous version is improved; the equivalence principle, which says that the exponential stability in moment of an anhysteretic stochastic system infers the same property of the corresponding hysteretic system, is extended to the cases with the newly propos...
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作者：Rakovic, Sasa V.; Zhang, Sixing
作者单位：Beijing Institute of Technology
摘要：This article creates a numerical platform for practical utility of the recently introduced theoretical framework of robust Minkowski-Lyapunov functions. Systems of affine inequalities and equalities whose feasibility verifies the robust Lyapunov nature of polyhedral Minkowski functions with respect to the recently introduced robust Minkowski-Lyapunov inequality are derived. The theoretically exact verification of the robust Minkowski-Lyapunov inequality in the polyhedral setting is reduced to ...
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作者：Sereshki, Z. Tavanaei; Talebi, H. A.; Abdollahi, F.
作者单位：Amirkabir University of Technology
摘要：This article presents an analytical approach to solve the infinite horizon H-infinity tracking control problem in nonlinear systems with unknown drift dynamics. A new quadratic cost function is presented that includes a feed-forward term and compensates the unknown nonlinearity effects in drift dynamics to improve the tracking performance. It is shown that the proposed cost function can be stated in another form. This enables us to extract the optimal solution without solving Hamilton-Jacobi-I...
