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The DAO to MetaControl for Metasystems in Metaverses:The System of Parallel Control systems for Knowledge Automation and Control Intelligence in CPSS

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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

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Social influence and spread dynamics in social networks

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Frontiers of Computer Science 2012年第5期6卷 611-620页

作者： Xiaolong ZHENG Yongguang ZHONG Daniel ZENG Fei-Yue WANG State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Management Science and Engineering Qingdao UniversityQingdao 266071China

Social networks often serve as a critical medium for information dissemination, diffusion of epidemics, and spread of behavior, by shared activities or similarities be- tween individuals. Recently, we have witnessed an explosion of interest in studying social influence and spread dynamics in social networks. To date, relatively little material has been provided on a comprehensive review in this field. This brief survey addresses this issue. We present the current significant empirical studies on real social systems, including network construction methods, measures of network, and newly em- pirical results. We then provide a concise description of some related social models from both macro- and micro-level per- spectives. Due to the difficulties in combining real data and simulation data for verifying and validating real social sys- tems, we further emphasize the current research results of computational experiments. We hope this paper can provide researchers significant insights into better understanding the characteristics of personal influence and spread patterns in large-scale social systems.

关键词： social networks spread dynamics social influence computational experiment

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Generative Adversarial Networks:Introduction and Outlook

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 588-598页

作者： Kunfeng Wang Chao Gou Yanjie Duan Yilun Lin Xinhu Zheng Fei-Yue Wang IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Department of Computer Science and Engineering University of Minnesota Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning *** goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that *** their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application ***, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.

关键词： ACP approach adversarial learning generative adversarial networks(GANs) generative models parallel intelligence zero-sum game

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Implementation of a multi-link robotic dolphin with two 3-DOF flippers

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Journal of Computational Information systems 2011年第7期7卷 2601-2607页

作者： Shen, Fei Wei, Changming Cao, Zhiqiang Xu, De Yu, Junzhi Zhou, Chao State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

A robotic dolphin with a pair of 3-DOF flippers, two turning units and a multi-link oscillatory propulsion mechanism is designed. The mechanical, hardware and software designs of the robotic dolphin are given. The flippers are fixed on both sides of the anterior body and each one is endowed with the ability of lead-lag, feathering, and up-down motions. The yawing of the robotic dolphin is realized via controlling the two turning units. The multi-link oscillatory propulsion mechanism consists of four joints, in which the first joint adopts the structure of worm gear and shaft driven by a DC motor in order to provide large torque and the other three oscillatory hinge joints are directly driven by servos. The propulsion is achieved via the coordinated controlling of the four joints. The performance of the robotic dolphin is well verified in the experiments. Copyright © 2011 Binary Information Press.

关键词： DC motors

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Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1210-1220页

作者： Guojun Wang Jian Wu Rui He Bin Tian State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the Qingdao Academy of Intelligent Industries ShandongChina

Road boundary detection is essential for autonomous vehicle localization and decision-making,especially under GPS signal loss and lane *** road boundary detection in structural environments,obstacle occlusions and large road curvature are two significant ***,an effective and fast solution for these problems has remained *** solve these problems,a speed and accuracy tradeoff method for LiDAR-based road boundary detection in structured environments is *** proposed method consists of three main stages:1)a multi-feature based method is applied to extract feature points;2)a road-segmentation-line-based method is proposed for classifying left and right feature points;3)an iterative Gaussian Process Regression(GPR)is employed for filtering out false points and extracting boundary *** demonstrate the effectiveness of the proposed method,KITTI datasets is used for comprehensive experiments,and the performance of our approach is tested under different road *** experiments show the roadsegmentation-line-based method can classify left,and right feature points on structured curved roads,and the proposed iterative Gaussian Process Regression can extract road boundary points on varied road shapes and traffic ***,the proposed road boundary detection method can achieve real-time performance with an average of 70.5 ms per frame.

关键词： 3D-LiDAR autonomous vehicle object detection point cloud road boundary

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A Recurrent Attention and Interaction Model for Pedestrian Trajectory Prediction

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1361-1370页

作者： Xuesong Li Yating Liu Kunfeng Wang Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the University of Chinese Academy of SciencesBeijing 100049China College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The movement of pedestrians involves temporal continuity,spatial interactivity,and random *** a result,pedestrian trajectory prediction is rather *** existing trajectory prediction methods tend to focus on just one aspect of these challenges,ignoring the temporal information of the trajectory and making too many *** this paper,we propose a recurrent attention and interaction(RAI)model to predict pedestrian *** RAI model consists of a temporal attention module,spatial pooling module,and randomness modeling *** temporal attention module is proposed to assign different weights to the input sequence of a target,and reduce the speed deviation of different *** spatial pooling module is proposed to model not only the social information of neighbors in historical frames,but also the intention of neighbors in the current *** randomness modeling module is proposed to model the uncertainty and diversity of trajectories by introducing random *** conduct extensive experiments on several public *** results demonstrate that our method outperforms many that are state-ofthe-art.

关键词： Deep learning long short-term memory(LSTM) recurrent attention and interaction(RAI)model trajectory prediction

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Development and path planning of a novel unmanned surface vehicle system and its application to exploitation of Qarhan Salt Lake

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Science China(Information Sciences) 2019年第8期62卷 195-197页

作者： Zhibin XUE Jincun LIU Zhengxing WU Sheng DU Shihan KONG Junzhi YU College of Chemical Engineering Qinghai University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences

Qarhan Salt Lake is rich in mineral resources, such as sodium chloride, potassium, and magnesium [1].At present, liquid mine exploiting is the main exploitation form for the Qarhan Salt Lake. Salt mining ships with mining equipments are widely used to exploit carnallite which is located at the bottom of pools. Conventionally, workmen utilize rude ferric sampler to collect carnallite samples

关键词： USV simulation Development and path planning of a novel unmanned surface vehicle system and its application to exploitation of Qarhan Salt Lake

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A Kind of Lean Approach for Removing Wastes From Non-Manufacturing Process With Various Facilities

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 307-315页

作者： Guangyu Xiong Xiuqin Shang Gang Xiong Timo R.Nyberg IEEE the Silk Road Business School Sanya University the Department of Industrial Engineering and Management School of ScienceAalto University the State Key Laboratory for Management and Controlof Complex Systems Institute of AutomationChinese Academy of Sciences(CAS) Qingdao Academy of Intelligent Industries the Cloud Computing Center CAS the Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationCAS the School of Science at Aalto University

It is important to identify and remove the wastes not only from manufacturing process, but also from nonmanufacturing process. In the last several decades, significant research achievements and practice benefits have been achieved about removing wastes from manufacturing process. Since the1990 s, some researchers and lean practitioners have paid more attention to removing waste from non-manufacturing *** on the authors' research work and industrial practice, the paper introduces a kind of lean approach for removing waste from non-manufacturing process. In its case study, the order handling process in a value chain is described with respect to a factory and its downstream distribution centers(DCs). The paper proposes a lean approach solution for creating the improved order handling process, and analyze how great improvements in performance can be achieved. As a result, the significant achievement has created a win-win scenario for both the nonmanufacturing process in a factory and non-manufacturing facilities(like DCs) across the value chain. It demonstrates that improvements have been made by removing waste from the non-manufacturing process that takes place within a factory as well as with external participants through the whole value chain. Likewise, the proposed lean approach has helped the case companies to achieve greater levels of efficiency and more benefits. Finally, some conclusions are drawn.

关键词： Lean approach non-manufacturing process optimized order handling process removing wastes value chain win-win scenario

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Direct Adaptive Output Feedback Control for MIMO Uncertain Nonlinear Discrete-Time systems Based on Neural Networks

Direct Adaptive Output Feedback Control for MIMO Uncertain N...

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第三十二届中国控制会议

作者： YANG Xiong LIU Derong WANG Ding The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479900305

This paper develops a novel neural-network-based direct adaptive control scheme for a class of multi-input-multioutput uncertain nonlinear discrete-time(DT) systems in the presence of unknown bounded *** employing feedback linearization methods,neural network(NN) approximation can cancel the nonlinearity of the DT ***,the weights of NNs are directly updated online instead of preliminary offline *** addition,unlike most literatures,the condition for persistent excitation is *** on Lyapunov's direct method,both tracking errors and weight estimates are guaranteed to be uniformly ultimately bounded,while keeping the closed-loop system ***,an example is provided to demonstrate the effectiveness of the proposed approach.

关键词： Uncertain nonlinear system Output feedback Multi-input-multi-output Direct adaptive control Neural network

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A Learning Optimal Control Scheme for Robust Stabilization of a Class of Uncertain Nonlinear systems

A Learning Optimal Control Scheme for Robust Stabilization o...

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第三十二届中国控制会议

作者： WANG Ding LIU Derong LI Hongliang YANG Xiong The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479900305

In this paper, a novel learning optimal control scheme is established to design the robust controller of a class of uncertain nonlinear systems. The robust control problem is transformed into the optimal control problem by properly choosing a cost function that reflects the uncertainty, regulation, and control. Then, the online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman （HJB） equation by introducing a critic neural network. The approximate expression of the optimal control policy can be derived directly. Moreover, the closed-loop system is proved to be uniformly ultimately bounded. The equivalence of the neural-network-based HJB solution of the optimal control problem and the solution of the robust control problem is developed as well. Finally, an example is provided to verify the effectiveness of the constructed approach.

关键词： Adaptive dynamic programming Neural networks Optimal control Robust control Uncertain nonlinear systems

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