期刊,自动化学报（英文版） 2024年卷5期_国家学术搜索

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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

主办单位：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

出版周期：双月刊

国际刊号：2329-9266

电子邮箱：yan.ou@ia.ac.cn

电　　话：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。

正式出版

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Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Zheng ChenShizhao ZhouChong ShenLitong Lyu...

1213-1226页

查看更多>>摘要：Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-deriva-tive(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effec-tive alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particu-larly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differen-tiating of position measurement,the low-pass filtering is com-monly used,but it will definitely restrict the closed-loop band-width of the whole system.To avoid this problem and realize bet-ter control performance,this paper proposes a novel observer-based adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertain-ties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop sys-tem robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a perfor-mance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop band-width breakthrough,which is limited by low-pass filtering in full-state-feedback control.

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Deterministic Learning-Based Neural PID Control for Nonlinear Robotic Systems

Qinchen YangFukai ZhangCong Wang

1227-1238页

查看更多>>摘要：Traditional proportional-integral-derivative(PID)controllers have achieved widespread success in industrial appli-cations.However,the nonlinearity and uncertainty of practical systems cannot be ignored,even though most of the existing research on PID controllers is focused on linear systems.There-fore,developing a PID controller with learning ability is of great significance for complex nonlinear systems.This article proposes a deterministic learning-based advanced PID controller for robot manipulator systems with uncertainties.The introduction of neu-ral networks(NNs)overcomes the upper limit of the traditional PID feedback mechanism's capability.The proposed control scheme not only guarantees system stability and tracking error convergence but also provides a simple way to choose the three parameters of PID by setting the proportional coefficients.Under the partial persistent excitation(PE)condition,the closed-loop system unknown dynamics of robot manipulator systems are accurately approximated by NNs.Based on the acquired knowl-edge from the stable control process,a learning PID controller is developed to further improve overall control performance,while overcoming the problem of repeated online weight updates.Sim-ulation studies and physical experiments demonstrate the validity and practicality of the proposed strategy discussed in this article.

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国家科技期刊平台
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维普

Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

Ke LiShunyi ZhaoBiao HuangFei Liu...

1239-1249页

查看更多>>摘要：In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensional-ity,and directly exploiting holistic information for state inference is not always computationally affordable.This paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems.The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the cal-culation of error covariance with immense dimensions.After that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state segmentation.More-over,the computational cost and error covariance of the pro-posed algorithm are analyzed analytically to show its distinct fea-tures compared with several existing methods.Simulation results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

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国家科技期刊平台
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Privacy-Preserving Consensus-Based Distributed Economic Dispatch of Smart Grids via State Decomposition

Wei ChenGuo-Ping Liu

1250-1261页

查看更多>>摘要：This paper studies the privacy-preserving dis-tributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart grids.To prevent power-sensitive information from being disclosed,a pri-vacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is transmitted.Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical con-straints while preventing sensitive information from being eaves-dropped.To this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach.In particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode.Furthermore,rigorous analysis is given to show privacy-preserving performance against internal and exter-nal eavesdroppers.Finally,case studies illustrate the feasibility and validity of the developed algorithm.

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国家科技期刊平台
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NSTL
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Stabilization Controller of An Extended Chained Nonholonomic System With Disturbance:An FAS Approach

Zhongcai ZhangGuangren Duan

1262-1273页

查看更多>>摘要：This study examines the stabilization issue of exten-ded chained nonholonomic systems(ECNSs)with external dis-turbance.Unlike the existing approaches,we transform the con-sidered system into a fully actuated system(FAS)model,simpli-fying the stabilizing controller design.We implement a separate controller design and propose exponential stabilization controller and finite-time stabilization controller under finite-time distur-bance observer(FTDO)for the two system inputs.In addition,we discuss the specifics of global stabilization control design.Our approach demonstrates that two system states exponentially or asymptotically converge to zero under the provided switching sta-bilization control strategy,while all other system states converge to zero within a finite time.

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国家科技期刊平台
NETL
NSTL
万方数据
维普

State-Based Opacity Verification of Networked Dis-crete Event Systems Using Labeled Petri Nets

Yifan DongNaiqi WuZhiwu Li

1274-1291页

查看更多>>摘要：The opaque property plays an important role in the operation of a security-critical system,implying that pre-defined secret information of the system is not able to be inferred through partially observing its behavior.This paper addresses the verifi-cation of current-state,initial-state,infinite-step,and K-step opac-ity of networked discrete event systems modeled by labeled Petri nets,where communication losses and delays are considered.Based on the symbolic technique for the representation of states in Petri nets,an observer and an estimator are designed for the verification of current-state and initial-state opacity,respectively.Then,we propose a structure called an I-observer that is com-bined with secret states to verify whether a networked discrete event system is infinite-step opaque or K-step opaque.Due to the utilization of symbolic approaches for the state-based opacity ver-ification,the computation of the reachability graphs of labeled Petri nets is avoided,which dramatically reduces the computa-tional overheads stemming from networked discrete event sys-tems.

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