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arXiv 2021年

作者： Song, Yue Liu, Tao Hill, David J. The Department of Control Science and Engineering Tongji University Shanghai201804 China The National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201210 China The Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai200120 China Hong Kong The HKU Shenzhen Institute of Research and Innovation Shenzhen China The Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC3000 Australia The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

This paper incorporates a continuous-type network flexibility into chance constrained economic dispatch (CCED). In the proposed model, both power generations and line susceptances are continuous variables to minimize the expected generation cost and guarantee a low probability of constraint violation in terms of generations and line flows under renewable uncertainties. From the analytical form of CCED, we figure out the mechanism of network flexibility against uncertainties-while renewable uncertainties shrink the usable line capacities and aggravate transmission congestion, network flexibility mitigates congestion by re-routing the base-case line flows and reducing the line capacity shrinkage caused by uncertainties. Further, we propose an alternate iteration solver for this problem. By duality theory, we set up a master problem in the form of second-order cone programming to optimize generation dispatch scheme and a subproblem in the form of linear programming to optimize line susceptances. A satisfactory solution can be obtained efficiently by alternately solving these two problems. The proposed method applies to both Gaussian uncertainty and non-Gaussian uncertainty by means of Gaussian mixture model. The case studies on the IEEE 14-bus system and IEEE 118-bus system suggest that network flexibility can significantly improve operational economy while ensuring security under uncertainties. © 2021, CC BY.

关键词： Second-order cone programming

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Neural Network-Based Prescription of Chinese Herbal Medicines

Neural Network-Based Prescription of Chinese Herbal Medicine...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Wen Zhao Weikai Lu Chang'en Zhou Zuoyong Li Haoyi Fan Xuejuan Lin Zhaoyang Yang Candong Li School of Traditional Chinese Medicine Fujian University of Traditional Chinese Medicine Fuzhou China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781728194202

Objective: To develop a neural network model that recommends traditional Chinese medicine (TCM) herbal prescriptions. Methods: We constructed a new dataset of diagnosis and treatment knowledge from the Treatise on Febrile Diseases. Based on TCM's logical principles of “syndrome differentiation” and “state recognition”, a back-propagation neural network model is proposed that simulates clinical diagnosis and treatment. Results: The proposed model is a four-layer BP neural network. Experiments on the constructed dataset show that the proposed method achieved the best precision, recall, and F1-scores. Conclusion: The proposed method provides much more accurate herbal prescription recommendations than logistic regression.

关键词： Neural networks Education Clinical diagnosis Information technology Logistics Diseases

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Urban Digital Twins for intelligent Road Inspection

Urban Digital Twins for Intelligent Road Inspection

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IEEE International Conference on Big Data

作者： Rui Fan Yikang Zhang Sicen Guo Jiahang Li Yi Feng Shuai Su Yanting Zhang Wenshuo Wang Yu Jiang Mohammud Junaid Bocus Xingyi Zhu Qijun Chen the Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous Systems and State Key Laboratory of Intelligent Autonomous Systems Robotics & Artificial Intelligence Laboratory (RAIL) Tongji University Shanghai P. R. China Department of Computer Science & Technology Donghua University Shanghai P. R. China Department of Civil Engineering McGill University Montreal Canada CTO office at ClearMotion Billerica MA USA Department of Electrical & Electronic Engineering the University of Bristol BS8 1UB U.K Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji University Shanghai P. R. China

ISBN: (纸本)9781665480468

Urban digital twin (UDT) technologies offer new opportunities for intelligent road inspection (IRI). This paper first reviews the state-of-the-art algorithms used in the two key components of UDT-based IRI systems: (1) multi-temporal, multi-dimension, multi-score, and heterogeneous road data acquisition, and (2) road distress detection. This paper then summarizes the UDTIRI competition, organized in conjunction with IEEE Bigdata 2022. More details on our competition are available at ***/view/udtiri-workshop/bigdata-2022.

关键词： Roads Data acquisition Inspection Big Data Rough surfaces Digital twins

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Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

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Sum-Rate Maximization of RIS-Aided Multi-User MIMO systems with Statistical CSI

arXiv

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arXiv 2021年

作者： Zhang, Huan Ma, Shaodan Shi, Zheng Zhao, Xin Yang, Guanghua The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The Institute of Physical Internet The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Department of Electrical and Computer Engineering University of Macau Taipa 999078 China

This paper investigates a reconfigurable intelligent surface (RIS)-aided multi-user multiple-input multiple-output (MIMO) system by considering only the statistical channel state information (CSI) at the base station (BS). We aim to maximize its sum-rate via the joint optimization of beamforming at the BS and phase shifts at the RIS. However, the multi-user MIMO transmissions and the spatial correlations make the optimization cumbersome. For tractability, a deterministic approximation is derived for the sum-rate under a large number of the reflecting elements. By adopting the approximate sum-rate for maximization, the optimal designs of the transmit beamforming and the phase shifts can be decoupled and solved in closed-forms individually. More specifically, the global optimality of the transmit beamforming can be guaranteed by using water-filling algorithm and a sub-optimal solution of phase shifts can be obtained by using projected gradient ascent (PGA) algorithm. By comparing to the case of the instantaneous CSI assumed at the BS, the proposed algorithm based on statistical CSI can achieve comparable performance but with much lower complexity and signaling overhead, which is more affordable and appealing for practical applications. Moreover, the impact of spatial correlation is thoroughly examined by using majorization theory. © 2021, CC BY.

关键词： MIMO systems

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Lyapunov characterizations of input-to-state stability for discrete-time switched systems via finite-step Lyapunov functions

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IFAC-PapersOnLine 2020年第2期53卷 2016-2021页

作者： Maryam Sharifi Navid Noroozi Rolf Findeisen School of Electrical and Computer Engineering University of Tehran Tehran Iran Laboratory for Systems Theory and Automatic Control Otto-von-Guericke University Magdeburg Germany

This paper addresses Lyapunov characterizations of input-to-state stability for nonlinear switched discrete-time systems via finite-step Lyapunov functions with respect to closed sets. The use of finite-step Lyapunov functions permits not-necessarily input-to-state stable systems in the systems family, while input-to-state stability of the resulting switched system is ensured. The result is generally presented for systems under arbitrary switching. It additionally covers the case of constrained switchings. We illustrate the effectiveness of our results by application to networked control systems with periodic scheduling policies under a priori known and dwell time-based switching mechanism.

关键词： Discrete-time switched systems Lyapunov methods input-to-state stability finite-step Lyapunov functions networked control systems

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Natural Language Processing for Smart Healthcare

arXiv

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arXiv 2021年

作者： Zhou, Binggui Yang, Guanghua Shi, Zheng Ma, Shaodan The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural language processing (NLP) plays a key role in smart healthcare due to its capability of analysing and understanding human language. In this work, we review existing studies that concern NLP for smart healthcare from the perspectives of technique and application. We first elaborate on different NLP approaches and the NLP pipeline for smart healthcare from the technical point of view. Then, in the context of smart healthcare applications employing NLP techniques, we introduce representative smart healthcare scenarios, including clinical practice, hospital management, personal care, public health, and drug development. We further discuss two specific medical issues, i.e., the coronavirus disease 2019 (COVID-19) pandemic and mental health, in which NLP-driven smart healthcare plays an important role. Finally, we discuss the limitations of current works and identify the directions for future works. Copyright © 2021, The Authors. All rights reserved.

关键词： Artificial intelligence

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MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divide-and-conquer Deformation

MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divi...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Tang, Ying Sun, Shengtao Wu, Ben Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781728168531

The reconstruction of surface mesh from point cloud is compute-intensive but also very important step in the remanufacturing and personalization industries. With more 3D scanners providing lower cost and higher resolution, further detailed point clouds can be gathered without so much effort as before. In manufacturing, there are databases which contain the origin 3D design models of the products. How to utilize the design model data for swift production of related products remains a problem for remanufacturing and customization. In order to develop a knowledge-based way of handling this problem, editing or deforming an existing mesh to match the target is an effective way of easing the workload. In this paper, we introduce a divide-and -conquer process which segments the depth scan data and then find the best match in the database as its source of deformation. The segmentation is performed on 3D point level using global features extracted by 3D CNN. After that we find best match to our knowledge with the same features to acquire a fast meshing of the target object by deforming the existing parts from the match. The deformation of parts are being done sequentially. For further performance improvement, we present a deformation training method employing transfer learning on segment editing process. © 2020 IEEE.

关键词： Image reconstruction

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Sensor-less Complex System control of PMSM Based on Improved SMO

Sensor-less Complex System Control of PMSM Based on Improved...

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作者： Yingjie Xiong Anna Wang Tao Zhang College Of Information Science and Engineering Northeastern University Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology

The sensor-less control system of PMSM is complicated,and it is of great significance to carry out accurate mathematical modeling and simulation *** is small in size,high in efficiency,and low in noise,so it is very popular in AC motor *** have been widely used in various electrical appliances such as machine tools,robots,and household *** order to reduce the high-frequency chatter of the sensor-less control strategy of permanent magnet synchronous motors,a sensor-less control method based on improved SMO is *** back-EMF component in the static coordinate system is obtained through the *** backEMF component undergoes closed-loop feedback to eliminate the high-frequency *** back-EMF component is calculated by an improved PLL to obtain the position and speed of the rotor to improve system *** the end of the article,the feasibility is proved by comparing it with the simulation of conventional SMO-PLL.

关键词： PMSM SMO with closed-loop feed back improved PLL

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Extended Dissipative control for Drill-String systems with Input Time-Varying Delays 38

Extended Dissipative Control for Drill-String Systems with I...

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第三十八届中国控制会议

作者： Chengda Lu Min Wu Luefeng Chen Aoxue Yang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Software and Electrical Engineering Swinburne University of Technology

ISBN: (纸本)9781728123295;9789881563972

The objective of this paper is to design an extended dissipative controller for drill-string systems by taking into account input time-delays. A multi-degree-of-freedom lumped parameter model is established for the drill-string and a state space model in perturbation coordinates is derived correspondingly. By using the Lyapunov-Krasovskii functional method, two sufficient conditions are provided to make extended dissipativity analysis of the drill-string and design a suitable extended dissipative controller for the system. The effectiveness of our results is verified through a numerical example.

关键词： Drill-string extended dissipative control time-delay

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