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作者：Jiang, Yi; Liu, Lu; Feng, Gang
作者单位：City University of Hong Kong
摘要：This note investigates the adaptive linear quadratic control problem (ALQCP) for stochastic discrete-time (DT) linear systems with unmeasurable multiplicative and additive noises. A data-driven value iteration algorithm is developed to solve the stochastic algebraic Riccati equation (SARE) that results from the concerned problem and to simultaneously obtain the optimal feedback policy. The proposed algorithm directly uses online data to solve the ALQCP based on an unbiased estimator and an ini...
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作者：Wang, Lingfei; Chen, Guanpu; Bernardo, Carmela; Hong, Yiguang; Shi, Guodong; Altafini, Claudio
作者单位：Chinese Academy of Sciences; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Royal Institute of Technology; Linkoping University; Tongji University; University of Sydney
摘要：In this article, we propose and solve a social power game, i.e., a strategic game formulated on an opinion dynamics model and in which the agents aim to maximize their social power. As model we consider the concatenated Friedkin-Johnsen (FJ) model, which describes opinion evolution over a sequence of discussion events, while as actions we take the stubbornness coefficients, which can be freely chosen by the agents in order to maximize their social power, here corresponding to the utility funct...
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作者：Yilmaz, Cemal Tugrul; Krstic, Miroslav
作者单位：University of California System; University of California San Diego
摘要：Extremum seeking, an online model-free optimization algorithm with traditionally exponential convergence, was recently advanced by Poveda and coauthors to fixed-time convergence, using nonsmooth time-invariant feedback. In this article, we introduce an alternative time-varying prescribed-time extremum seeking (PT-ES) approach to reaching the optimum in a user-assignable prescribed time (PT), independent of the initial condition of the estimator. Instead of conventional sinusoidal probing signa...
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作者：Jimenez-Pastor, Antonio; Toller, Daniele; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea
作者单位：Aalborg University; IMT School for Advanced Studies Lucca; Technical University of Denmark
摘要：Positive systems naturally arise in situations where the model tracks physical quantities. Although the linear case is well understood, analysis and controller design for nonlinear positive systems remain challenging. Model reduction methods can help tame this problem. Here, we propose a notion of model reduction for a class of positive bilinear systems with (bounded) matrix and exogenous controls. Our reduction, called proper positive lumping, aggregates the original system such that states o...
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作者：Wang, Zheming; Berger, Guillaume O.; Jungers, Raphael M.
作者单位：Zhejiang University of Technology; Universite Catholique Louvain
摘要：We tackle uniform state feedback control of switched linear systems under arbitrary switching using scenario optimization. We propose a data-driven control framework, in which scenario programs are formulated to compute stabilizing state feedback control relying on a finite set of observations of trajectories with quadratic and sum of squares (SOS) Lyapunov functions. We do not require the exact dynamical model or the switching signal, and as a consequence, we aim at solving uniform stabilizat...
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作者：Liu, Wei; Zhao, Huanyu; Shen, Hao; Xu, Shengyuan; Park, Ju H.
作者单位：Huaiyin Institute of Technology; Yeungnam University; Anhui University of Technology; Nanjing University of Science & Technology
摘要：This article tackles the predefined-time control problem for nonlinear systems subject to preassigned performance metrics (PPMs) and state constraints. To meet the PPMs and state constraints, the preassigned performance control-based barrier Lyapunov functions are designated to acquire the performance metrics and the satisfaction of state constraints. The proposed control approach combines the predefined-time control with the recursive design of command-filter backstepping to achieve the prese...
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作者：Takai, Shigemasa; Kumar, Ratnesh
作者单位：University of Osaka; Iowa State University
摘要：In the authors' earlier work, the notion of inference-observability was introduced to characterize the existence of decentralized supervisors that perform multilevel inferencing against self-ambiguity and the ambiguities of others to jointly arrive at a correct control decision. When the property of $N$-inference-observability holds, $N$-levels of inferencing are needed. We show in this article that the class of $N$-inference-observable languages increases strictly monotonically as the paramet...
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作者：An, Liwei; Yang, Guang-Hong
作者单位：Northeastern University - China; Northeastern University - China
摘要：This article studies the problem of collision/obstacle avoidance in the distributed cooperative output regulation of nonlinear multiagent systems (MASs). First, a nonlinear distributed command governor equipped by two dynamical barrier functions is constructed to generate safe command signals. Then, a filtering-based distributed command tracking control scheme is proposed. It is shown that the MAS adaptively reconfigures its formation shape in a distributed way when entering into the barrier f...
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作者：Fu, Chengcheng; Zhang, Hao; Huang, Chao; Wang, Zhuping; Yan, Huaicheng
作者单位：Tongji University; Tongji University; East China University of Science & Technology
摘要：This note investigates the cooperative output regulation problem for linear periodically time-varying systems. The problem is divided into two subproblems: solving periodic differential Sylvester equations (PDSEs) and designing a suitable time-varying distributed controller to stabilize an augmented multiagent system. First, the solvability of the PDSEs is discussed under an observability condition. Then, a dynamic output-feedback controller based on the internal model principle is proposed, w...
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作者：Holtorf, Flemming; Schafer, Frank; Arnold, Julian; Rackauckas, Christopher V.; Edelman, Alan
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); University of Basel
摘要：The limits of quantum feedback control have immediate consequences for quantum information science at large, yet remain largely unexplored. Here, we combine quantum filtering theory and moment-sum-of-squares techniques to construct a hierarchy of convex optimization problems that furnish monotonically improving, computable bounds on the best attainable performance for a broad class of quantum feedback control problems. These bounds may serve as witnesses of fundamental limitations, optimality ...
