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arXiv 2021年

作者： Liu, Wenjie Sun, Jian Wang, Gang Bullo, Francesco Chen, Jie State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Department of Control Science and Engineering Tongji University Shanghai201804 China Mechanical Engineering Department The Center of Control Dynamical Systems and Computation UC Santa BarbaraCA93106-5070 United States

This paper is concerned with the problem of stabilizing continuous-time linear time-invariant systems subject to quantization and Denial-of-Service (DoS) attacks. In this context, two DoS-induced challenges emerge with the design of resilient encoding schemes, namely, the coupling between encoding strategies of different signals, and the synchronization between the encoder and decoder. To address these challenges, a novel structure that is equipped with a deadbeat controller as well as a delicate transmission protocol for the input and output channels, co-designed leveraging the controllability index, is put forward. When both input and output channels are subject to DoS attacks and quantization, the proposed structure is shown able to decouple the encoding schemes for input, output, and estimated output signals. This property is further corroborated by designing encoding schemes as well as conditions that ensure exponential stability of the closed-loop system. On the other hand, when only the output channel is subject to network phenomenon, the proposed structure can achieve exponential stabilization without acknowledgment (ACK) signals, in contrast to existing ACK-based results. Finally, a numerical example is given to demonstrate the practical merits of the proposed approach as well as the theory. © 2021, CC BY.

关键词： Denial-of-service attack

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EnsembleFollower: A Hybrid Car-Following Framework Based on Hierarchical Planning and Reinforcement Learning

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IEEE Transactions on Vehicular Technology 2025年

作者： Han, Xu Chen, Xianda Zhu, Meixin Cai, Pinlong Zhou, Jianshan Chu, Xiaowen Data Science and Analytics Thrust Information Hub Guangzhou China Intelligent Transportation Thrust Systems Hub Guangzhou China Sensing and Computation for Ubiquitous Internet of Things Guangdong Provincial Key Lab of Integrated Communication China Southeast University School of Transportation Nanjing211189 China Shanghai Artificial Intelligence Laboratory Shanghai China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems & Safety Control State Key Laboratory of Intelligent Transportation Systems China Beihang University School of Transportation Science and Engineering Beijing100191 China

Car-following models have made significant contributions to our understanding of longitudinal driving behavior. However, they often exhibit limited accuracy and flexibility, as they cannot fully capture the complexity inherent in car-following processes, or may struggle in unseen scenarios due to their reliance on confined driving skills present in training data. It is worth noting that each car-following model possesses its own strengths and weaknesses depending on specific driving scenarios. Therefore, we propose EnsembleFollower, a closed-loop hierarchical planning framework for achieving human-like autonomous car-following. The EnsembleFollower framework involves a high-level Reinforcement Learning-based agent responsible for judiciously managing multiple low-level models (such as intelligent Driver Model and Gipps model) according to the current state, either by selecting an appropriate car-following model to perform an action or by allocating different weights across all primitive models. Moreover, we propose a jerk-constrained kinematic model for more convincing microscopic traffic simulations. We evaluate the proposed method based on real-world driving data from the HighD dataset. The experimental results illustrate that EnsembleFollower yields an improved accuracy of human-like behavior and achieves effectiveness in combining hybrid models, demonstrating that our proposed framework can handle diverse driving conditions by leveraging the strengths of various car-following models. © 1967-2012 IEEE.

关键词： Deep reinforcement learning

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Tunable coupling of a quantum phononic resonator to a transmon qubit with flip-chip architecture

arXiv

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arXiv 2024年

作者： Ruan, Xinhui Li, Li Liang, Guihan Zhao, Silu Wang, Jia-Heng Bu, Yizhou Chen, Bingjie Song, Xiaohui Li, Xiang Zhang, He Wang, Jinzhe Zhao, Qianchuan Xu, Kai Fan, Heng Liu, Yu-Xi Zhang, Jing Peng, Zhihui Xiang, Zhongcheng Zheng, Dongning Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Integrated Circuits Tsinghua University Beijing100084 China Hefei National Laboratory Hefei230088 China School of Automation Science and Engineering Xi'an Jiaotong University Xi’an710049 China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi’an710049 China CAS Center for Excellence in Topological Quantum Computation School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China

A hybrid system with tunable coupling between phonons and qubits shows great potential for advancing quantum information processing. In this work, we demonstrate strong and tunable coupling between a surface acoustic wave (SAW) resonator and a transmon qubit based on galvanic-contact flip-chip technique. The coupling strength varies from 2π×7.0 MHz to -2π×20.6 MHz, which is extracted from different vacuum Rabi oscillation frequencies. The phonon-induced ac Stark shift of the qubit at different coupling strengths is also shown. Our approach offers a good experimental platform for exploring quantum acoustics and hybrid systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Hybrid systems

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Erratum to “An ADRC Method for Noncascaded Integral Systems Based on Algebraic Substitution Method and Its Structure”

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Mathematical Problems in Engineering 2019年第1期2019卷

作者： Zhijian Huang Yudong Li Yihua Liu Bowen Sui Guichen Zhang Lab of Intelligent Control and Computation Shanghai Maritime University Shanghai 201306 *** Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI 02881 USAuri.edu

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Mathematical model of brain tumour growth with drug resistance

arXiv

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arXiv 2020年

作者： Trobia, José Tian, Kun Batista, Antonio M. Grebogi, Celso Ren, Hai-Peng Santos, Moises S. Protachevicz, Paulo R. Borges, Fernando S. Szezech, José D. Viana, Ricardo L. Caldas, Iberê L. Iarosz, Kelly C. Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’anPR710048 China Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom Xi’an Technological University Xi’anPR710021 China Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Faculdade de Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil

Brain tumours are masses of abnormal cells that can grow in an uncontrolled way in the brain. There are different types of malignant brain tumours. Gliomas are malignant brain tumours that grow from glial cells and are identified as astrocytoma, oligodendroglioma, and ependymoma. We study a mathematical model that describes glia-neuron interaction, glioma, and chemotherapeutic agent. In this work, we consider drug sensitive and resistant glioma cells. We show that continuous and pulsed chemotherapy can kill glioma cells with a minimal loss of neurons. © 2020, CC BY.

关键词： Tumors

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Effects of drug resistance in the tumour-immune system with chemotherapy treatment

arXiv

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arXiv 2020年

作者： Trobia, José Gabrick, Enrique C. Seifert, Evandro G. Borges, Fernando S. Protachevicz, Paulo R. Szezech, José D. Iarosz, Kelly C. Santos, Moises S. Caldas, Iberê L. Tian, Kun Ren, Hai-Peng Grebogi, Celso Batista, Antonio M. Graduate Program in Science - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Faculty of Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná Ponta Grossa Paraná84016-210 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Xi’an Technological University Xi’an710021 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom

Cancer is a term used to refer to a large set of diseases. The cancerous cells grow and divide and, as a result, they form tumours that grow in size. The immune system recognise the cancerous cells and attack them, though, it can be weakened by the cancer. One type of cancer treatment is chemotherapy, which uses drugs to kill cancer cells. Clinical, experimental, and theoretical research has been developed to understand the dynamics of cancerous cells with chemotherapy treatment, as well as the interaction between tumour growth and immune system. We study a mathematical model that describes the cancer growth, immune system response, and chemotherapeutic agents. The immune system is composed of resting cells that are converted to hunting cells to combat the cancer. In this work, we consider drug sensitive and resistant cancer cells. We show that the tumour growth can be controlled not only by means of different chemotherapy protocols, but also by the immune system that attacks both sensitive and resistant cancer cells. Furthermore, for all considered protocols, we demonstrate that the time delay from resting to hunting cells plays a crucial role in the combat against cancer cells. Copyright © 2020, The Authors. All rights reserved.

关键词： Chemotherapy

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