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自动化学报（英文版）
中国自动化学会、中国科学院自动化研究所、中国科技出版传媒股份有限公司
自动化学报（英文版）

中国自动化学会、中国科学院自动化研究所、中国科技出版传媒股份有限公司

双月刊

2329-9266

yan.ou@ia.ac.cn

010-82544459

自动化学报（英文版）/Journal IEEE/CAA Journal of Automatica SinicaCSCDCSTPCD北大核心SCI
查看更多>>《自动化学报》（英文版），刊名为 IEEE/CAA Journal of Automatica Sinica (JAS)，创刊于2014年，由中国自动化学会、中国科学院自动化研究所主办，与IEEE合作，报道自动控制、人工智能、机器人等领域热点和前沿方向的研究成果。JAS被SCI, EI, Scopus等数据库收录，是ESI刊源期刊，也是自动化与控制系统领域唯一的中国主办Q1区SCI期刊。2019年首个JCR影响因子5.129，在自动化与控制领域全球63种SCI期刊中排名第11（前17%），位列Q1区。2019年CiteScore为8.3，位于所属各领域Q1区前列；国内外综合他引影响因子为6.688，在自动化、计算机领域的中国英文期刊中排名第1。
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    Securing the Future after PagerBombs:Lifecycle Protection of Smart Devices via Blockchain Intelligence

    Fei LinQinghua NiJing YangJuanjuan Li...
    2355-2358页
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Pager Explosion:Cybersecurity Insights and Afterthoughts

    Chuan ShengWanlun MaQing-Long HanWei Zhou...
    2359-2362页
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Analysis and Control of Frequency Stability in Low-Inertia Power Systems:A Review

    Changjun HeHua GengKaushik RajashekaraAmbrish Chandra...
    2363-2383页
    查看更多>>摘要：Power electronic-interfaced renewable energy sources(RES)exhibit lower inertia compared to traditional syn-chronous generators.The large-scale integration of RES has led to a significant reduction in system inertia,posing significant challenges for maintaining frequency stability in future power systems.This issue has garnered considerable attention in recent years.However,the existing research has not yet achieved a com-prehensive understanding of system inertia and frequency stabil-ity in the context of low-inertia systems.To this end,this paper provides a comprehensive review of the definition,modeling,analysis,evaluation,and control for frequency stability.It com-mences with an exploration of inertia and frequency characteris-tics in low-inertia systems,followed by a novel definition of fre-quency stability.A summary of frequency stability modeling,analysis,and evaluation methods is then provided,along with their respective applicability in various scenarios.Additionally,the two critical factors of frequency control—energy sources at the system level and control strategies at the device level—are examined.Finally,an outlook on future research in low-inertia power systems is discussed.
      原文链接:
    • 国家科技期刊平台
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    Disturbance Rejection for Systems With Uncertain-ties Based on Fixed-Time Equivalent-Input-Disturbance Approach

    Qun LuXiang WuJinhua SheFanghong Guo...
    2384-2395页
    查看更多>>摘要：This paper presents a fixed-time equivalent-input-disturbance(EID)approach to deal with the problem of robust output-feedback control for perturbed uncertain systems.This method uses the basic structure of the conventional EID approach and treats uncertainties and disturbances as a lumped distur-bance on the control-input channel.A fixed-time state observer enables state estimation,which resolves the causality issue in an EID-based control system,is finished in a fixed time.An implicit Lyapunov function,the homogeneity with dilation,the input-to-state stability,and the small-gain theorem are used to analyze the convergence and robustness of the EID-based system with mea-surement noise.Numerical and experimental results are pre-sented to demonstrate the effectiveness and superiority of the pro-posed method.
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    • 国家科技期刊平台
    • NETL
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    Distributed Fixed-Time Optimal Energy Management for Microgrids Based on a Dynamic Event-Triggered Mechanism

    Feisheng YangJiaming LiuXiaohong Guan
    2396-2407页
    查看更多>>摘要：The article investigates the optimal energy manage-ment(OEM)problem for microgrids.To figure out the problem in fixed time and alleviate communication load with limited resources,this article devises a novel fixed-time stability lemma and an event-triggered(ET)fixed-time distributed OEM approach.Using Lyapunov stability theory,the distributed approach has been proven to converge in fixed time and the upper bound on convergence time can be derived without depen-dence on the initial states.The dynamic ET method is raised to dynamically adjust the triggering threshold and reduce commu-nication redundancy.In addition,Zeno behavior is avoided.Sim-ulations are given to show the effectiveness and advantage of the designed distributed OEM method.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Safe Q-Learning for Data-Driven Nonlinear Optimal Control With Asymmetric State Constraints

    Mingming ZhaoDing WangShijie SongJunfei Qiao...
    2408-2422页
    查看更多>>摘要：This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an optimal performance.First,we design an augmented utility function consisting of an adjustable positive definite control obstacle function and a quadratic form of the next state to ensure the safety and optimality.Second,by exploiting a pre-designed admissible policy for initialization,an off-policy stabilizing value iteration Q-learning(SVIQL)algo-rithm is presented to seek the safe optimal policy by using offline data within the safe region rather than the mathematical model.Third,the monotonicity,safety,and optimality of the SVIQL algorithm are theoretically proven.To obtain the initial admissi-ble policy for SVIQL,an offline VIQL algorithm with zero ini-tialization is constructed and a new admissibility criterion is established for immature iterative policies.Moreover,the critic and action networks with precise approximation ability are established to promote the operation of VIQL and SVIQL algo-rithms.Finally,three simulation experiments are conducted to demonstrate the virtue and superiority of the developed safe Q-learning method.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Cas-FNE:Cascaded Face Normal Estimation

    Meng WangJiawan ZhangJiayi MaXiaojie Guo...
    2423-2434页
    查看更多>>摘要：Capturing high-fidelity normals from single face images plays a core role in numerous computer vision and graph-ics applications.Though significant progress has been made in recent years,how to effectively and efficiently explore normal pri-ors remains challenging.Most existing approaches depend on the development of intricate network architectures and complex cal-culations for in-the-wild face images.To overcome the above issue,we propose a simple yet effective cascaded neural network,called Cas-FNE,which progressively boosts the quality of pre-dicted normals with marginal model parameters and computa-tional cost.Meanwhile,it can mitigate the imbalance issue between training data and real-world face images due to the pro-gressive refinement mechanism,and thus boost the generaliza-tion ability of the model.Specifically,in the training phase,our model relies solely on a small amount of labeled data.The earlier prediction serves as guidance for following refinement.In addi-tion,our shared-parameter cascaded block employs a recurrent mechanism,allowing it to be applied multiple times for optimiza-tion without increasing network parameters.Quantitative and qualitative evaluations on benchmark datasets are conducted to show that our Cas-FNE can faithfully maintain facial details and reveal its superiority over state-of-the-art methods.The code is available at https://github.com/AutoHDR/CasFNE.git.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Multi-View Dynamic Kernelized Evidential Clustering

    Jinyi XuZuowei ZhangZe LinYixiang Chen...
    2435-2450页
    查看更多>>摘要：It is challenging to cluster multi-view data in which the clusters have overlapping areas.Existing multi-view cluster-ing methods often misclassify the indistinguishable objects in overlapping areas by forcing them into single clusters,increasing clustering errors.Our solution,the multi-view dynamic kernel-ized evidential clustering method(MvDKE),addresses this by assigning these objects to meta-clusters,a union of several related singleton clusters,effectively capturing the local imprecision in overlapping areas.MvDKE offers two main advantages:firstly,it significantly reduces computational complexity through a dynamic framework for evidential clustering,and secondly,it adeptly handles non-spherical data using kernel techniques within its objective function.Experiments on various datasets confirm MvDKE's superior ability to accurately characterize the local imprecision in multi-view non-spherical data,achieving better efficiency and outperforming existing methods in overall perfor-mance.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    High-Order Fully Actuated System Models for Strict-Feedback Systems With Increasing Dimensions

    Xiang XuGuang-Ren Duan
    2451-2462页
    查看更多>>摘要：This paper mainly addresses control problems of strict-feedback systems(SFSs)with increasing dimensions.Com-pared with the commonly-considered SFSs where the subsystems have the same dimension,we aim to handle more complex cases,i.e.,the subsystems in the considered SFSs are assumed to have increasing dimensions.By transforming the systems into high-order fully-actuated system(HOFAS)models,the stabilizing con-trollers can be directly given.Besides first-order SFSs,second-order and high-order SFSs are also considered.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Human Observation-Inspired Universal Image Acquisition Paradigm Integrating Multi-Objective Motion Planning and Control for Robotics

    Haotian LiuYuchuang TongZhengtao Zhang
    2463-2475页
    查看更多>>摘要：Image acquisition stands as a prerequisite for scruti-nizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being con-fined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seam-lessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versa-tile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energy-based adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold opti-mization and adaptive weight adjustment to improve the smooth-ness and accuracy of imaging trajectory and posture.Addition-ally,a multi-optimization control scheme based on a meta-heuris-tic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据