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Cross-correlations between signal's components

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Chinese Physics B 2025年第2期34卷 483-494页

作者： Quankun Zhao Sen Li Changgui Gu Haiying Wang Huijie Yang Department of systems science University of Shanghai for Science and TechnologyShanghai 200093China

Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.

关键词： coupling structure cross-correlation matrix component correlation network

An autonomous dynamic recovery technology for autonomous underwater vehicles based on unmanned surface vehicles

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science China(Technological sciences) 2025年第2期68卷 315-317页

作者： Yueying WANG Yiqi SHI Guanghui WEN Huaicheng YAN school of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China Department of systems science School of MathematicsSoutheast UniversityNanjing 210096China school of Information science and Engineering East China University of Science and TechnologyShanghai 200237China

Autonomous underwater vehicles(AUVs) have attracted considerable attention due to their vast potential applications, such as offshore oil exploration, underwater rescue, military reconnaissance, and marine scientific ... 详细信息

关键词： underwater autonomous battery

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Chattering-Free Fault-Tolerant Cluster Control and Fault Direction Identification for HIL UAV Swarm With Pre-Specified Performance

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 183-197页

作者： Pei-Ming Liu Xiang-Gui Guo Jian-Liang Wang Daniel Coutinho Lihua Xie the Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing the Shunde Graduate school of University of science and Technology Beijing IEEE Autonomous Intelligent systems Department Hangzhou Innovation Institute of Beihang University the Department of Automation and systems Universidade Federal de Santa Catarina the school of Electrical and Electronic Engineering Nanyang Technological University

In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the presence of possible nonidentical and unknown direction faults(NUDFs) in the yaw *** control strategy begins with the design of a pre-specified performance event-triggered observer for each individual *** observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer *** is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.

关键词： Chattering-free cluster consensus fault direction identification human-in-the-loop (HIL) nonidentical and unknown direction faults (NUDFs) pre-specified performance swarm unmanned aerial vehicles (UAVs)

Dual-phase interface engineering via parallel modulation strategy for highly reversible Zn metal batteries

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Journal of Energy Chemistry 2025年第2期101卷 163-174页

作者： Zhean Bao Yang Wang Kun Zhang Guosheng Duan Leilei Sun Sinan Zheng Bin Luo Zhizhen Ye Jingyun Huang school of Materials science and Engineering State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University Institute of Wenzhou Zhejiang University Institute of Thermal science and Power systems Zhejiang University Longmen Laboratory of Luoyang

The reversibility and stability of aqueous Zn metal batteries（AZMBs） are largely limited by Zn dendrites and interfacial parasitic ***,we propose a parallel modulation strategy to boost the reversibility of the Zn anode by introducing N,N,N',N'-tetramethylchloroformamidinium hexafluorophosphate（TCFH） as an additive in the *** is composed of PF6-and TN+with opposite ***6-can spontaneously induce the in-situ generation of ZnF2solid electrolyte interface（SEI） on the anode,which can improve the transport kinetics of Zn2+at the interface,thus promoting the rapid and uniform deposition of Zn as well as inhibiting the growth of *** addition,TN+is enriched at the anode surface during Zn deposition through the anchoring effect,which brings a reconfiguration of the ion/molecule *** anchored-TN+reduces the concentrations of H2O and SO42-,sufficiently restraining the parasitic *** to the dual-phase interface engineering constructed of PF6-and TN+in parallel,the symmetric cell with the proposed electrolyte survives long cycling stability over750 h at 20 mA cm-2,10 mAh *** study offers a distinct viewpoint to the multidimensional optimization of Zn anodes for high-performance AZMBs.

关键词： Anchoring effect Aqueous Zn metal batteries Electrolyte additive Solid electrolyte interface Zn anode

Quantile-based optimization under uncertainties for complex engineering structures using an active learning basis-adaptive PC-Kriging model

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Chinese Journal of Aeronautics 2025年第1期38卷 340-352页

作者： Yulian GONG Jianguo ZHANG Dan XU Ying HUANG school of Reliability and systems Engineering Beihang UniversityBeijing 100191China

The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount of sampling simulation *** this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed,in order to relieve the computational burden and enhance the predictive accuracy of a *** active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO ***,five engineering cases have been implemented,including a benchmark RBDO problem,three high-dimensional explicit problems,and a high-dimensional implicit *** with Support Vector Regression(SVR),Kriging,and polynomial chaos expansion models,results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.

关键词： Reliability-based design optimization Quantile-based Basis-adaptive PC-Kriging Complex engineering structures Active learning Uncertainty

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Residential Energy Scheduling With Solar Energy Based on Dyna Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 403-413页

作者： Kang Xiong Qinglai Wei Hongyang Li the Institute of systems Engineering Macau University of Science and Technology IEEE the State Key Laboratory of Multimodal Artificial Intelligence systems Institute of Automation Chinese Academy of Sciences the school of Artificial Intelligence University of Chinese Academy of Sciences

Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.

关键词： Adaptive dynamic programming (ADP) dynamic residential scenarios optimal residential energy management smart grid

Domain generalization with semi-supervised learning for people-centric activity recognition

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science China(Information sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking systems of AI school of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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The optimal control theory——a scientific approach to fundamentally solving control problems

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science China(Information sciences) 2025年第1期68卷 389-391页

作者： Huanshui ZHANG school of Electrical and Automation Engineering Shandong University of Science and Technology school of Control science and Engineering Shandong University

The maximum principle has bridged mathematical optimization to optimal control,ushering in significant developments and refinements in optimal control theory,notably during the 1960s with the advent of linear quadratic (LQ)control and linear quadratic estimation (LQE).This progression propelled optimal control theory into further advancements,encompassing stochastic control,robust/H-infinity control,model predictive control (MPC),networked control,and reinforcement learning *** control,established upon a rigorous mathematical foundation,extends static optimization theory to dynamic systems,exhibiting scientific essence,unity,and ***,since its inception,optimal control theory has served as an indispensable core role across all control-related domains,including communication-constrained control in networked systems,consensus control,cooperative control,and reinforcement learning control.

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On-Policy and Off-Policy Value Iteration Algorithms for Stochastic Zero-Sum Dynamic Games

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Journal of systems science & Complexity 2025年第01期 421-435页

作者： GUO Liangyuan WANG Bing-Chang ZHANG Ji-Feng school of Control science and Engineering Shandong University school of Automation and Electrical Engineering Zhongyuan University of Technology Key Laboratory of systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences

This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown dynamics. On-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games, where the system dynamics is not required. By analyzing the value function iterations, the convergence of the model-based algorithm is shown. The equivalence of several types of value iteration algorithms is established. The effectiveness of model-free algorithms is demonstrated by a numerical example.

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