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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1899-1908页

作者： fei-yue wang The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing100190Chi the Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao999078China

An investigation and outline of MetaControl and DeControl in Metaverses for control intelligence and knowledge automation are *** control with prescriptive knowledge and parallel philosophy is proposed as the starting point for the new control philosophy and technology,especially for computational control of metasystems in cyberphysical-social *** argue that circular causality,the generalized feedback mechanism for complex and purposive systems,should be adapted as the fundamental principle for control and management of metasystems with metacomplexity in ***,an interdisciplinary approach is suggested for MetaControl and DeControl as a new form of intelligent control based on five control metaverses:MetaVerses,MultiVerses,InterVerses,TransVerse,and DeepVerses.

关键词： MetaControl MetaSystems Metaverses CPSS DAO DeControl Prescriptive Control Parallel Control Computational Control Knowledge Automation Control Intelligence Parallel Intelligence

New Control Paradigm for Industry 5.0:From Big Models to Foundation Control and Management

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1643-1646页

作者： fei-yue wang IEEE the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

DO we need a fundamental change in our professional culture and knowledge foundation for control and automation?If so,what are necessary and critical steps we must take to ensure such a change would take place effecti... 详细信息

关键词： smoothly steps culture

The Metaverse of Mind:Perspectives on DeSci for DeEco and DeSoc

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2043-2046页

作者： fei-yue wang IEEE The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing100190China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao999078China

First of all, I would like to take this opportunity to express my sincere and deep thanks to our Editor-in-Chief, Professor Meng Chu Zhou, who took over my position after I was drafted for rejuvenating IEEE Transactions on Computational Social Systems in 2017. During the past five years, Meng Chu’s professional leadership and dedication has transformed IEEE/CAA Journal of Automatica Sinica(JAS) from its infancy to a young and high-impact publication in the world that is full of vitality and actively engaged by a group of talented and charged associate Ei Cs and editors, which is clearly demonstrated in Meng Chu’s farewell editorial [1]. I am very glad that Professor Qing-Long Han, an influential and leading scientist of the world-class in AI, control, automation, and intelligent science and technology from Australia, as well as a staunch supporter and great leader of this journal from its beginning, will take over the Ei C torch from Meng Chu next year, since I am extremely confident that our journal will reach a new high for its service and quality under his new leadership.

关键词： journal leadership Australia

New Chief, New Journey, New Excellence

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 1-2页

作者： fei-yue wang IEEE

After five years planning and working for its creation,and four years serving as its Founding Editor-in-Chief,it is time for me to step down and free IEEE/CAA Journal of Automatica Sinica to the new journey for its ne... 详细信息

关键词： New Journey New Chief New Excellence Man

The TAO of Blockchain Intelligence for Intelligent Web 3.0

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2183-2186页

作者： Juanjuan Li fei-yue wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

WE are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish.[1]–[3].In this new epoch,the collaboration of data and knowledge,humans and machines,actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation,unveiling an open future full of boundless ***,the value of dispersed data extends far beyond passive storage and application.

关键词： Web TAO knowledge

From Parallel Plants to Smart Plants:Intelligent Control and Management for Plant Growth

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 161-166页

作者： Mengzhen Kang fei-yue wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of Automation.

关键词： Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development

From Plant Modeling to Narrative Science:Growing and Enjoying Scientific Fruits Naturally and Humanistically

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2522-2524页

作者： fei-yue wang IEEE Macau University of Science and Technology the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences

Dear Editor,Modeling is the first and essential step for control and automation,and large models, from current Chat GPT or large language models(LLMs) to future large knowledge models of knowledge automation,would be the foundation model and infrastructure intelligence for coming intelligent industries and smart societies.

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Determination of Polynomial Degree in the Regression of Drug Combinations

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IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 41-47页

作者： Boqian wang Xianting Ding fei-yue wang School of Biomedical Engineering Shanghai Jiao Tong University IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

Studies on drug combinations are becoming more and more popular in the past few decades, with the development of computer and algorithms. One of the most common methods in optimizing drug combinations is regression of a polynomial model based on certain number of experimental observations. In this paper, we study how to determine the degree of polynomials in different circumstances of drug combination optimization. Using cross-validation, we have found that in most cases, a high degree results in failures of accurate prediction, named overfitting. An anti-noise test has also revealed that polynomial model with high degree tends to be less resistant to random errors in the observations. © 2014 Chinese Association of Automation.

关键词： Acoustics Random errors Regression analysis

A Scholar of Dignity:Remembering Peter Luh

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1895-1897页

作者： fei-yue wang Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100190China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

It was a shock and disbelief to learn of Peter's death last *** me,he was so fit in his figure,so healthy in his lifestyle,so mild and mindful in his social behavior,and so devout in his religious belief,......,I had ... 详细信息

关键词： religious Scholar belief

Parallel Control for Optimal Tracking via Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1662-1674页

作者： Jingwei Lu Qinglai Wei fei-yue wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078 Qingdao Academy of Intelligent Industries Qingdao 266109China

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback ***,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied *** address this problem,an augmented system and an augmented performance index function are proposed ***,the general nonlinear system is transformed into an affine nonlinear *** difference between the optimal parallel control and the optimal state feedback control is analyzed *** is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index ***,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function *** stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference ***,the effectiveness of the developed optimal parallel control method is verified in two cases.

关键词： Adaptive dynamic programming(ADP) nonlinear optimal control parallel controller parallel control theory parallel system tracking control neural network(NN)