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2022 Chinese Automation Congress, CAC 2022

作者： Tan, Cong Lin, Mingduo Xia, Hongbing Zhao, Bo Xu, Yancai School of Systems Science Beijing Normal University Beijing100875 China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781665465335

A novel fault-tolerant tracking control (FTTC) approach for affine nonlinear systems is developed from the perspective of zero-sum differential games (ZSDG) to deal with unknown multiplicative actuator failures in this paper. By regarding the control input and the multiplicative actuator failure as two players of a zero-sum game, a performance index function reflecting the trajectory tracking error, the control policy and the unknown failure is established. To handle the tracking Hamilton-Jacobi-Isaacs (HJI) equation associated with the established performance index function, a critic neural network is utilized. Then, the Nash equilibrium solution can be obtained, and the FTTC is achieved. The stability of the faulty nonlinear system is examined through Lyapunov-based approach. Finally, simulation results of a spring system is provided to ensure the utility and the realizability of the ZSDG-based FTTC approach. © 2022 IEEE.

关键词： Nonlinear systems

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Assimilation of ASCAT Sea Surface Wind Retrievals with Correlated Observation Errors

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Journal of Meteorological Research 2021年第3期35卷 478-489页

作者： Boheng DUAN Weimin ZHANG Xiaofeng YANG Mengbin ZHU College of Meteorology and Oceanology National University of Defense TechnologyChangsha 410073 Laboratory of Software Engineering for Complex Systems Changsha 410073 State Key Laboratory of Remote Sensing Science Chinese Academy of SciencesBeijing 100101 Hainan Key Laboratory of Earth Observation Sanya 572029 Beijing Institute of Applied Meteorology Beijing 100029

data assimilation systems usually assume that the observation errors of wind components, i.e., u(the longitudinal component) and v(the latitudinal component), are uncorrelated. However, since wind components are derived from observations in the form of wind speed and direction(spd and dir), the observation errors of u and v are correlated. In this paper, an explicit expression of the observation errors and correlation for each pair of wind components are derived based on the law of error propagation. The new data assimilation scheme considering the correlated error of wind components is implemented in the Weather Research and Forecasting data Assimilation(WRFDA) system. Besides, adaptive quality control(QC) is introduced to retain the information of high wind-speed observations. Results from real data experiments assimilating the Advanced Scatterometer(ASCAT) sea surface winds suggest that analyses from the new data assimilation scheme are more reasonable compared to those from the conventional one, and could improve the forecasting of Typhoon Noru.

关键词： data assimilation Advanced Scatterometer(ASCAT) wind components correlated observation error

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An LMI approach to design robust fault detection filter for uncertain Lur'e singularly perturbed systems

An LMI approach to design robust fault detection filter for ...

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第43届中国控制会议

作者： Lei Liu Wenjie Dou Ying Yang Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology State Key Lab for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of EngineeringPeking University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper, the robust fault detection filter(RFDF) design problem for uncertain Lur'e singularly perturbed systems(SPSs) with unknown inputs is studied. Firstly, an optimal residual generator is constructed as a reference model, and the design of the RFDF for the system is formulated as an H∞ model matching problem. Secondly, based on the linear matrix inequality(LMI) theory, the sufficient conditions for the augmented system to be absolutely stable and satisfy the H∞ performance index are derived. Then an algorithm is proposed to solve the optimization problem, based on this, the specific parameters of the RFDF are obtained by using the LMI toolbox, and the fault detection method based on residual signal is obtained. Finally, a numerical example is given to verify the feasibility and effectiveness of the proposed results.

关键词： Lur'e Singularly Perturbed systems Fault detection filter Model matching H∞ optimization Linear matrix inequality(LMI)

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data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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An Efficient Deep Transfer Learning Network for Characterization of Stroke Patients' Motor Execution from Multi-Channel EEG-Recordings 46

An Efficient Deep Transfer Learning Network for Characteriza...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Samuel, Oluwarotimi Williams Asogbon, Mojisola Grace Kulwa, Frank McEwan, Alistair A. Aboyeji, Sunday Timothy Khushaba, Rami Fang, Peng Li, Guanglin University of Derby School of Computing and Data Science Research Centre DerbyDE22 3AW United Kingdom SIAT-CAS Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Sydney University Australian Centre for Field Robotics ChippendaleNSW2008 Australia

ISBN: (纸本)9798350371499

Recent advances in stroke rehabilitation technology have been focused on developing Intelligent Rehabilitation Robots (IRR) that can effectively engage post-stroke patients (PSP) in intuitive motor training for full function recovery. Most existing rehabilitation robots incorporate functionalities that are passive in nature, constraining PSP to predetermined trajectories that often deviate from patients' limb movement intentions, consequently hindering recovery. To resolve this issue, a robust deep-transfer learning driven network (DTLN) is developed to adequately characterize PSP's motion intention signatures from neural oscillations towards achieving intuitive and active training. Thus, we investigated and proposed the utilization of mu-frequency spectrum (muFS) based CWT approach for Scalograms construction, which serves as inputs to the DTLN model that characterizes multiple classes of PSP's motor execution signatures from multi-channel electroencephalography (EEG) recordings. Then, we evaluated the proposed method using EEG data from six PSP and compared the decoding results to those of related approaches under similar experimental settings. The proposed method resulted in a significant increment of 10.84 % - 13.19% decoding accuracy across stroke patients and better convergence in comparison to other methods. Additionally, the method exhibited distinct task separability for individual motor execution signature across patients. In conclusion, our method offers a consistently accurate decoding of motor tasks that could enable intuitively active robotic training in PSPs with impaired motor function. © 2024 IEEE.

关键词： Brain computer interface

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Efficient ILT via Multi-Level Lithography Simulation 23

Efficient ILT via Multi-Level Lithography Simulation

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Shuyuan Sun Fan Yang Bei Yu Li Shang Xuan Zeng State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China and School of Microelectronics Fudan University Shanghai China Chinese University of Hong Kong Hong Kong China State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China and China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9798350323481

Inverse Lithography Technology (ILT) is a widely investigated method to improve the yield of chip manufacturing. However, high computational complexity and difficulty in fabricating curvilinear shapes have hindered the widespread adoption of ILT. This paper presents an efficient ILT framework, including a multi-level resolution method for simulation acceleration, a downsampling strategy for mask optimization, and an improved mask binary function to improve mask printability. Experimental results show that the proposed method outperforms state-of-the-art methods with at least a 33.8% reduction in L2 loss and a 15.5% reduction in PVBand.

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SYNC: SAFETY-AWARE NEURAL CONTROL FOR STABILIZING STOCHASTIC DELAY-DIFFERENTIAL EQUATIONS 11

SYNC: SAFETY-AWARE NEURAL CONTROL FOR STABILIZING STOCHASTIC...

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11th International Conference on Learning Representations, ICLR 2023

作者： Zhang, Jingdong Zhu, Qunxi Yang, Wei Lin, Wei School of Mathematical Sciences SCMS SCAM CCSB Fudan University Shanghai200433 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Shanghai Artificial Intelligence Laboratory China MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Fudan University Shanghai200032 China

Stabilization of the systems described by stochastic delay-differential equations (SDDEs) under preset conditions is a challenging task in the control community. Here, to achieve this task, we leverage neural networks to learn control policies using the information of the controlled systems in some prescribed regions. Specifically, two learned control policies, i.e., the neural deterministic controller (NDC) and the neural stochastic controller (NSC), work effectively in the learning procedures that rely on, respectively, the well-known LaSalle-type theorem and the newly-established theorem for guaranteeing the stochastic stability in SDDEs. We theoretically investigate the performance of the proposed controllers in terms of convergence time and energy cost. More practically and significantly, we improve our learned control policies through considering the situation where the controlled trajectories only evolve in some specific safety set. The practical validity of such control policies restricted in safety set is attributed to the theory that we further develop for safety and stability guarantees in SDDEs using the stochastic control barrier function and the spatial discretization. We call this control as SYNC (SafetY-aware Neural Control). The efficacy of all the articulated control policies, including the SYNC, is demonstrated systematically by using representative control problems. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Controllers

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AI4S Based on DeSci: Reference Model and Research Issues

AI4S Based on DeSci: Reference Model and Research Issues

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IEEE International Conference on systems, Man and Cybernetics

作者： Wenwen Ding Juanjuan Li Rui Qin Sangtian Guan Fei-Yue Wang Faculty of Innovation Engineering Macau University of Science and Technology Macau China The State Key Laboratory for Management and Control of Complex Systems The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

The rise of Artificial Intelligence for science (AI4S) has highlighted the importance and urgency of ensuring open-ness, fairness, impartiality, diversity, and sustainability in scientific systems. Existing scientific systems, referred to as Centralized science (CeSci), are built on centralized organizational structures and top-down institutional frameworks, which are lagging behind the development and practical requirements of AI4S. To address these limitations, AI4S needs to embrace a new scientific organizational and operational paradigm, namely Decentralized science (DeSci). It can provide strong support to AI4S via effectively addressing issues such as information silos, biases, unfair distribution, and monopolies and promoting multidisciplinary, interdisciplinary, and trans disciplinary cooperation in science. Based on these considerations, this paper presents the framework of AI4S based on DeSci and explores its potential application scenarios and research issues. The research can provide effective guidance for the development of scientific systems.

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Using Lock-Free Design for Throughput-Optimized Cache Eviction

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Proceedings of the ACM on Measurement and Analysis of Computing systems 2025年第2期9卷 1-28页

作者： Dong, Chao Wang, Fang Jiang, Hong Feng, Dan Huazhong University of Science and Technology Key Laboratory of Information Storage System Wuhan National Laboratory for Optoelectronics Engineering Research Center of data storage systems and Technology School of Computer Science and Technology Ministry of Education of China Hubei Wuhan China University of Texas at Arlington Department of Computer Science and Engineering ArlingtonTX United States

In large-scale information systems, storage device performance continues to improve while workloads expand in size and access characteristics. This growth puts tremendous pressure on caches and storage hierarchy in terms of concurrent throughput. However, existing cache eviction policies often struggle to provide adequate concurrent throughput due to their reliance on coarse-grained locking mechanisms and complex data structures. This paper presents a practical approach to cache eviction algorithm design, called Mobius, that optimizes the concurrent throughput of caches and reduces cache operation latency by utilizing lock-free data structures, while maintaining comparable hit ratios. Mobius includes two key designs. First, Mobius employs two lock-free FIFO queues to manage cache items, ensuring that all cache operations are executed efficiently in parallel. Second, Mobius integrates a consecutive detection mechanism that merges multiple modifications during eviction into a single operation, thereby reducing data races. Extensive evaluations using both synthetic and real-world workloads from high-concurrency clusters demonstrate that Mobius achieves a concurrent-throughput improvement ranging from 1.2× to 8.5× over state-of-the-art methods, while also maintaining lower latency and comparable cache hit ratios. The implementation of Mobius in CacheLib and RocksDB highlights its effectiveness in enhancing cache performance in practical scenarios. © 2025 ACM.

关键词： keyways

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动力学问题中矩阵函数的高效算法

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Acta Mechanica Sinica 2023年第8期39卷 137-147页

作者：吴锋朱力赵悦琳章恺琳阎军钟万勰施庆华 Department of Mechanics State Key Laboratory of Structural Analysis of Industrial Equipment Dalian University of Technology Dalian 116023 China State Key Laboratory for Turbulence & Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing 100871 China Yunnan Machinery Research and Design Institute China National Machinery Institute Group Kunming 650000 China

本文基于Paterson-Stockmeyer(PS)算法和过滤技术提出了一种能精确和高效计算动力学问题中矩阵函数的算法.借助对截断误差和过滤引误差的分析,探究了计算中的误差增长规律,并基于此给出了自适应过滤阈值,使得提出的算法能更加高效地达... 详细信息

本文基于Paterson-Stockmeyer(PS)算法和过滤技术提出了一种能精确和高效计算动力学问题中矩阵函数的算法.借助对截断误差和过滤引误差的分析,探究了计算中的误差增长规律,并基于此给出了自适应过滤阈值,使得提出的算法能更加高效地达到与原PS算法相似的精度.数值实验采用了包括30个不同带宽的随机矩阵,10个复杂网络动力学问题中的邻接矩阵来验证提出算法的效率与精度.数值实验的结果表明,提出的算法在计算所考虑的动力学问题的矩阵函数时能获得良好的精度和效率.

关键词：网络动力学矩阵函数动力学问题高效算法邻接矩阵随机矩阵截断误差过滤技术

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