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作者：Collins, Brandon C.; Xu, Shouhuai; Brown, Philip N.
作者单位：University of Colorado System; University of Colorado at Colorado Springs
摘要：The theory of learning in games has extensively studied situations where agents respond dynamically to each other in a static environment by optimizing a fixed utility function. However, real-world environments evolve as a result of past agent choices. Unfortunately, the analysis techniques that enabled a rich characterization of the emergent behavior of games played in static environments fail to cope with games played in dynamic environments. To address this problem, we develop a general fra...
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作者：Das, Ersin; Burdick, Joel W.
作者单位：California Institute of Technology
摘要：This article proposes a safety-critical control design approach for nonlinear control affine systems in the presence of matched and unmatched uncertainties. Our constructive framework couples control barrier function (CBF) theory with a new uncertainty estimator to ensure robust safety. We use the estimated uncertainty, along with a derived upper bound on the estimation error, for synthesizing CBFs and safety-critical controllers via a quadratic program-based feedback control law that rigorous...
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作者：Chen, Ziqin; Wang, Yongqiang
作者单位：Clemson University
摘要：The increasing usage of streaming data has raised significant privacy concerns in decentralized optimization and learning applications. To address this issue, differential privacy (DP) has emerged as a standard approach for privacy protection in decentralized online optimization. Regrettably, existing DP solutions for decentralized online optimization face the dilemma of trading optimization accuracy for privacy. In this article, we propose a local-DP solution for decentralized online optimiza...
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作者：de Oliveira, Paulo J.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.
摘要：This article addresses the problem of robust performance analysis and synthesis for uncertain linear systems with state-space matrices containing parameters in bounded intervals. The novelty of the approach relies on treating the interval bounds as optimization variables, leading to two significant results. First, an analysis tool that evaluates the sensitivity of closed-loop performance criteria, such as the H-infinity norm, with respect to the bounds, is presented. The second contribution is...
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作者：Chatterjee, Soham; Natarajan, Vivek
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Bombay
摘要：We consider the problem of finding an input signal which transfers a linear boundary controlled 1-D parabolic partial differential equation with spatially varying coefficients from a given initial state to a desired final state. The initial and final states have certain smoothness and the transfer must occur over a given time interval. We address this motion planning problem by first discretizing the spatial derivatives in the parabolic equation using the finite-difference approximation to obt...
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作者：Cros, Colin; Amblard, Pierre-Olivier; Prieur, Christophe; Da Rocha, Jean-Francois
作者单位：Universite de Toulouse; Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS); Thales Group
摘要：Linear fusion is a cornerstone of estimation theory. Implementing optimal linear fusion requires knowledge of the covariance of the vector of errors associated with all the estimators. In distributed or cooperative systems, the cross-covariance terms cannot be computed, and to avoid underestimating the estimation error, conservative fusions must be performed. A conservative fusion provides a fused estimator with a covariance bound that is guaranteed to be larger than the true, but computationa...
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作者：Bozkurt, Berk; Mahajan, Aditya; Nayyar, Ashutosh; Ouyang, Yi
作者单位：McGill University; University of Southern California
摘要：In this article, we consider the problem of designing a control policy for an infinite-horizon discounted cost Markov decision process M when we only have access to an approximate model M<^>. How well does an optimal policy pi<^>(star) of the approximate model perform when used in the original model M? We answer this question by bounding a weighted norm of the difference between the value function of pi<^>(star) when used in M and the optimal value function of M. We then extend our results and...
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作者：Leeman, Antoine P.; Kohler, Johannes; Zanelli, Andrea; Bennani, Samir; Zeilinger, Melanie N.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; European Space Agency
摘要：This article addresses the problem of finite horizon constrained robust optimal control for nonlinear systems subject to norm-bounded disturbances. To this end, the underlying uncertain nonlinear system is decomposed based on a first-order Taylor series expansion into a nominal system and an error (deviation) described as an uncertain linear time-varying system. This decomposition allows us to leverage system level synthesis to jointly optimize an affine error feedback, a nominal nonlinear tra...
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作者：Schmid, Niklas; Fochesato, Marta; Li, Sarah H. Q.; Sutter, Tobias; Lygeros, John
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Konstanz
摘要：We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard dynamic programming is inapplicable due to the time correlation of the joint chance constraints, which calls for non-Markovian, and possibly stochastic, policies. Hence, despite the popularity of this problem, solution approaches capable of providing provably optimal and easy-to-compute policies are still missing. We fill thi...
