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作者：Qi, Yiwen; Zhang, Simeng; Shi, Yang
作者单位：Fuzhou University; Shenyang Aerospace University; University of Victoria
摘要：This article studies active disturbance rejection control (ADRC) for uncertain switched systems under triggered learning. The novel triggered-learning ADRC framework optimizes the ADRC performance of switched systems through reinforcement learning (RL) and enables on-demand updates of neural networks with guidance from a predesigned trigger. The innovation of this article is mainly reflected in four aspects: First, the RL-based gain automatic update mechanism (i.e., the dual-gain optimization ...
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作者：Chang, Zeze; Jiao, Junjie; Li, Zhongkui
作者单位：Peking University; Technical University of Munich
摘要：This article considers a localized data-driven consensus problem for leader-follower multiagent systems with unknown discrete-time agent dynamics, where each follower computes its local control gain using only their locally collected state and input data. Both noiseless and noisy data-driven protocols are presented to achieve leader-follower consensus, by addressing the challenge of the heterogeneity in control gains caused by the localized data sampling and distinct parameters of agents. The ...
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作者：Sun, Qingdong; Yang, Guang-Hong
作者单位：Northeastern University - China; Northeastern University - China
摘要：This article studies the secure state estimation problem of continuous-time cyber-physical systems affected by sensor attacks and actuator faults, where the attackers do not target fixed transmission channels but instead stochastically select the channels to attack at each moment based on a specific Markov process. To address these challenges, a reduced-order observer is designed to simultaneously estimate the original system states, faults, and attacks, while ensuring that its observation err...
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作者：Xu, Yong; Wu, Zheng-Guang
作者单位：Beijing Institute of Technology; Zhejiang University
摘要：This article investigates the adaptive optimal output regulation of completely unknown linear time-invariant systems. First, a dynamic state feedback control policy with assured convergence rate requirement is developed such that the output regulation problem is transformed into a tractable optimization problem by incorporating the internal model. Then, an online-verifiable initial excitation-based dual-integrator-based learning algorithm is first proposed for establishing data-driven learning...
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作者：Alsalti, Mohammad; Lopez, Victor G.; Muller, Matthias A.
作者单位：Leibniz University Hannover
摘要：Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time linear time-invariant (LTI) systems by constructing nonminimal state vectors composed of past inputs and outputs. Depending on the system's complexity (order n, lag & ell; and number of outputs p), it was observed in several works that such an approach presents significant limitations. In particular, many works require to restrict the class of LTI systems to those satisfying the relatio...
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作者：Liu, Siyuan; Saoud, Adnane; Dimarogonas, Dimos V.
作者单位：Royal Institute of Technology; Mohammed VI Polytechnic University
摘要：This article considers the problem of controller synthesis of a fragment of signal temporal logic (STL) specifications for large-scale multiagent systems, where the agents are dynamically coupled and subject to collaborative tasks. A compositional framework based on continuous-time assume-guarantee contracts (AGCs) is developed to break the complex and large synthesis problem into subproblems of manageable sizes. We first show how to formulate the collaborative STL tasks as AGCs by leveraging ...
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作者：Villa, Eugenia; Breschi, Valentina; Tanelli, Mara
作者单位：Polytechnic University of Milan; Eindhoven University of Technology
摘要：While control theory can be pivotal in addressing societal challenges and helping policymakers in shaping our future, control schemes must incorporate elements of social justice to be both up to the task and fair. In turn, this requires the formulation of new constraints and control objectives and their integration into existing or new control design strategies. Devising a formally sound framework to ensure social fairness in control can enable a leap in understanding the implications of justi...
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作者：Yuan, Liwei; Ishii, Hideaki
作者单位：Hunan University; University of Tokyo
摘要：In this article, we study the problem of resilient consensus for a multiagent network, where some adversarial nodes attempt to prevent consensus of nonfaulty nodes by transmitting faulty values. Our approach is based on that of the so-called mean subsequence reduced (MSR) algorithm with a special emphasis on its use in agents capable to communicate with multihop neighbors. The MSR algorithm provides an effective technique for agents to achieve resilient consensus if the multiagent network sati...
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作者：Liu, Jiaxu; Chen, Song; Cai, Shengze; Xu, Chao; Chu, Jian
作者单位：Zhejiang University; Zhejiang University
摘要：This article delves into the investigation of a distributed aggregative optimization problem within a network. In this scenario, each agent possesses its own local cost function, which relies not only on the local state variable but also on an aggregated function of state variables from all agents. To expedite the optimization process, we amalgamate the heavy ball and Nesterov's accelerated method with distributed aggregative gradient tracking, resulting in the proposal of two innovative algor...
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作者：Zhang, Jin-Xi; Ding, Jinliang; Chai, Tianyou
作者单位：Northeastern University - China
摘要：This article is concerned with the problem of fault detection, isolation, and compensation for the multiple-input single-output nonlinear systems in the face of actuator failures. It is focused on the cases of possibly simultaneous failures and unknown inherent nonlinear dynamics, which render the existing solutions infeasible. To conquer these challenges, a novel fault-tolerant funnel control approach based on cyclic performance monitoring and switching mode rearrangement is devised. It detec...
