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作者：Hamza, Muhammad Amir; Mustafa, Ghulam; Shi, Dawei; Khan, Abdul Qayyum; Abid, Muhammad
作者单位：Pakistan Institute of Engineering & Applied Science; Beijing Institute of Technology
摘要：In this note, we characterize a family of discrete-time strictly causal stabilizing controllers for networked systems under nonuniform communication and network-induced delays. First, we absorb the feedback delay in the controller structure and parameterize a family of stabilizing controllers for the delay-free plant with some restrictions on the controller structure due to time delay. Then, we lift the feedback connection and choose the free parameter of the family in the lifted domain to inc...
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作者：Li, Yichuan; Voulgaris, Petros G.; Stipanovic, Dusan M.; Freris, Nikolaos M.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; Nevada System of Higher Education (NSHE); University of Nevada Reno; Chinese Academy of Sciences; University of Science & Technology of China, CAS
摘要：This article presents a family of algorithms for decentralized convex composite problems. We consider the setting of a network of agents that cooperatively minimize a global objective function composed of a sum of local functions plus a regularizer. Through the use of intermediate consensus variables, we remove the need for inner communication loops between agents when computing curvature-guided updates. A general scheme is presented, which unifies the analysis for a plethora of computing choi...
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作者：Xie, Huahui; Dai, Li; Sun, Zhongqi; Xia, Yuanqing
作者单位：Beijing Institute of Technology
摘要：Tube-based model predictive control (TMPC) is an outstanding control technique in robust control realms. However, the existing works are generally based on a priori known admissible sets of disturbances, i.e., disturbance constraint sets, the sizes of which are by default small enough such that the region of attraction is nonempty. If the size of the disturbance constraint set specified is too large, or even oversized in some particular direction, TMPC may not be capable of handling it and los...
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作者：Drummond, Ross; Valmorbida, Giorgio
作者单位：University of Sheffield; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS)
摘要：A class of Lyapunov functions for discrete-time Lurie systems with monotonic nonlinearities is proposed. The Lyapunov functions are composed of quadratic terms on the states and of the system's nonlinearities as well as Lurie-Postnikov-type integral terms. Crucially, positive definiteness of the matrix in the generalized quadratic form and positivity of the scaling terms of the Lurie-Postnikov integrals are relaxed in the stability conditions. Furthermore, they are used for regional stability ...
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作者：Kolarijani, Mohamad Amin Sharifi; Esfahani, Peyman Mohajerin
作者单位：Delft University of Technology
摘要：We propose two novel numerical schemes for the approximate implementation of the dynamic programming (DP) operation concerned with finite-horizon optimal control of discrete time systems with input-affine dynamics. The proposed algorithms involve discretization of the state and input spaces and are based on an alternative path that solves the dual problem corresponding to the DP operation. We provide error bounds for the proposed algorithms, along with a detailed analysis of their computationa...
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作者：Lee, Donggun; Deka, Shankar A.; Tomlin, Claire J.
作者单位：University of California System; University of California Berkeley; Royal Institute of Technology; University of California System; University of California Berkeley
摘要：This article presents a method that convexifies state-constrained optimal control problems in the control-input space. The proposed method enables convex programming methods to find the globally optimal solution even if costs and control constraints are nonconvex in control and convex in state, dynamics is nonaffine in control and convex in state, and state constraints are convex in state. Under the above conditions, generic methods do not guarantee to find optimal solutions, but the proposed ...
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作者：Nguyen, Hoai-Nam
作者单位：IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom SudParis
摘要：This article proposes a new model predictive control (MPC) control scheme for polytopic uncertain and/or time-varying systems with state and input constraints. The MPC policies we consider employ: 1) the intersection of ellipsoids to characterize the domain of attraction, 2) a time-varying Lyapunov function to bound from above the cost function, 3) a tailored alternating direction method of multipliers algorithm to solve efficiently the online optimization problem. With respect to other well-k...
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作者：Aghajan, Adel; Touri, Behrouz
作者单位：University of California System; University of California Santa Barbara; University of California System; University of California San Diego
摘要：We study the averaging-based distributed optimization solvers over random networks. We show a general result on the convergence of such schemes using weight matrices that are row-stochastic almost surely and column-stochastic in expectation for a broad class of dependent weight-matrix sequences. In addition to implying many of the previously known results on this domain, our work shows the robustness of distributed optimization results to link failure. Also, it provides a new tool for synthesi...
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作者：Berberich, Julian; Scherer, Carsten W.; Allgower, Frank
作者单位：University of Stuttgart; University of Stuttgart
摘要：We present a framework for systematically combining data of an unknown linear time-invariant system with prior knowledge on the system matrices or on the uncertainty for robust controller design. Our approach leads to linear matrix inequality (LMI)-based feasibility criteria that guarantee stability and performance robustly for all closed-loop systems consistent with the prior knowledge and the available data. The design procedures rely on a combination of multipliers inferred via prior knowle...
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作者：Wabersich, Kim Peter; Zeilinger, Melanie N.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：This article investigates the combination of model predictive control (MPC) concepts and posterior sampling techniques and proposes a simple constraint tightening technique to introduce cautiousness during explorative learning episodes. The provided theoretical analysis in terms of cumulative regret focuses on previously stated sufficient conditions of the resulting Cautious Bayesian MPC algorithm and shows Lipschitz continuity of the future reward function in the case of linear MPC problems. ...
