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第32届中国控制与决策会议

作者： Dingyi Ma Shijie Zhou Shigen Gao School of Electronic and Information Engineering Beijing Jiaotong University School of Computer and Information Technology Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

This paper presents a new composite error-based prescribed performance control（CEB-PPC） method for multiple trains cooperation with model uncertainties.A new prescribed performance function,which is capable of relaxing the requirements of known initial error and bringing in a large-enough initially allowable ranges,is *** key idea of CEB-PPC is the utilization of summation of "transformed" and "true" tracking error variables in proposed *** method also features with the ultimate boundaries are characterized by control gain and prescribed performance function（PPF） simultaneously,while only PPF in the traditional PPC *** results are given to demonstrate the effectiveness of proposed method in controlling cooperation of three trains.

关键词： prescribed performance control robust control composite error unknown initial error multiple trains cooperation

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Study on the economic evaluation model of wind, solar and energy storage combined power generation unit 3

Study on the economic evaluation model of wind, solar and en...

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3rd Annual International Conference on Network and Information Systems for computers, ICNISC 2017

作者： Wei, Xiao-Jing Lu, Qiong Department of Information and Communication State Grid Corporation of China Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781538616185

This paper studied and implemented a set of economic operation evaluation system of wind, solar and energy storage combined power generation unit. Firstly, according to the meteorological conditions, the unit output model was set up. Under the established coordinated operation strategy, wind, solar and energy storage combined power generation system was taken into grid as power generation unit with rated capacity. Then, starting from aspects of technical and economic benefit, financial benefit and social benefit, it constructed a comprehensive economic benefit index system. A comprehensive evaluation model was established by combining the subjective and objective value assignment method. Finally, through the development of the evaluation system, it completed the output simulation run on the power generation unit, in addition, it conducted visual analysis and display on evaluation results of different capacity matching schemes. The results showed that the research and development of the system could combine the performance characteristics of wind, solar and energy storage combined power generation technology to form the economic operation evaluation model of the power generation unit which conformed to the scale-up grid entrance, through the scientific process, it could form the evaluation result and then display this in a variety of chart forms to provide decision support for researchers. © 2019 IEEE.

关键词： Energy storage

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Deep Reinforcement Learning Based Massive Access Management for Ultra-Reliable Low-Latency Communications

arXiv

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arXiv 2020年

作者： Yang, Helin Xiong, Zehui Zhao, Jun Niyato, Dusit Yuen, Chau Deng, Ruilong School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore University of Technology and Design Singapore138682 College of Control Science and Engineering Zhejiang University Hangzhou310027 China

With the rapid deployment of the Internet of Things (IoT), fifth-generation (5G) and beyond 5G networks are required to support massive access of a huge number of devices over limited radio spectrum radio. In wireless networks, different devices have various quality-of-service (QoS) requirements, ranging from ultra-reliable low latency communications (URLLC) to high transmission data rates. In this context, we present a joint energy-efficient subchannel assignment and power control approach to manage massive access requests while maximizing network energy efficiency (EE) and guaranteeing different QoS requirements. The latency constraint is transformed into a data rate constraint which makes the optimization problem tractable before modelling it as a multi-agent reinforcement learning problem. A distributed cooperative massive access approach based on deep reinforcement learning (DRL) is proposed to address the problem while meeting both reliability and latency constraints on URLLC services in massive access scenario. In addition, transfer learning and cooperative learning mechanisms are employed to enable communication links to work cooperatively in a distributed manner, which enhances the network performance and access success probability. Simulation results clearly show that the proposed distributed cooperative learning approach outperforms other existing approaches in terms of meeting EE and improving the transmission success probability in massive access scenario. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Immunometabolism and potential targets in severe COVID-19 peripheral immune responses

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Asian Journal of Pharmaceutical Sciences 2021年第6期16卷 665-667页

作者： Shanshan Wang Xian Zeng Yali Wang Yuzong Chen Chaoxin Wang Dongzhi Zhuoma Fengying Zhang Yufen Zhao Qian Xuesen Collaborative Research Center of Astrochemistry and Space Life Sciences Institute of Drug Discovery TechnologyNingbo UniversityNingbo 315211China Department of Biological Medicines&Shanghai Engineering Research Center of Immunotherapeutics Fudan University School of PharmacyShanghai 201203China Bioinformatics and Drug Design Group Department of PharmacyNational University of Singapore117543Singapore Department of Computer Science Kansas State UniversityManhatten KS 66506USA Medical College Tibet University36 Jiangsu RoadLhasa 850011 China Key Lab of Agricultural Products Processing and Quality Control of Nanchang City Jiangxi Agricultural UniversityNanchang 330045China

In a recent single cell transcriptomic investigation of the peripheral immune responses of the patients with severe COVID-19[1],no substantial expression of pro-inflammatory cytokines has been identified in the peripheral monocytes and lymphocytes,while these peripheral immune cells exhibit phenotypes of heterogeneously expressed interferon-stimulated genes in certain COVID-19 *** genes may contribute to the inhibitory response to the viral entry,translation,replication and *** remain regarding why the peripheral cytokine production is constrained,what additional roles these peripheral immune cells may play in COVID-19 pathophysiology,and which potential targets can be explored for facilitating COVID-19 therapeutics.

关键词： metabolism interferon lymphocytes

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A survey on user-centric cell-free massive MIMO systemss

arXiv

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arXiv 2021年

作者： Chen, Shuaifei Zhang, Jiayi Zhang, Jing Björnson, Emil Ai, Bo School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Linköping University LinköpingSE-58183 Sweden Department of Computer Science KTH Royal Institute of Technology KistaSE-16440 Sweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Information Engineering Zhengzhou University Zhengzhou450001 China

The mobile data traffic has been exponentially growing during the last decades, which has been enabled by the densification of the network infrastructure in terms of increased cell density (i.e., ultra-dense network (UDN)) and/or increased number of active antennas per access point (AP) (i.e., massive multiple-input multiple-output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing data rate demands of the sixth generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations, respectively. Cell-free (CF) mMIMO, which combines the best aspects of UDN and mMIMO, is viewed as a key solution to this issue. In such systems, each user equipment (UE) is served by a preferred set of surrounding APs cooperatively. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO. As a starting point, the significance and the basic properties of CF mMIMO are highlighted. We then present the canonical framework, where the essential details (i.e., transmission procedure and mathematical system model) are discussed. Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms. After that, we discuss the practical issues when implementing CF mMIMO. Potential future directions are then pointed out. Finally, we conclude this paper with a summary of the key lessons learned in this field. This paper aims to provide a starting point for anyone who wants to conduct research on CF mMIMO for future wireless networks. © 2021, CC BY.

关键词： Feedback control

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Model free adaptive control scheme based on Elman neural network prediction

Model free adaptive control scheme based on Elman neural net...

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Chinese control Conference (CCC)

作者： Yong-wen LIAO Yi-ming MA Bao-wei CHEN Geng-da LI De-liang ZENG School of control and computer engineering North China Electric Power University Beijing Guodian New Energy Technology Research Institute Co. Ltd Beijing

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

Model free adaptive control (MFAC) is a typical data-driven control method. This method only uses the input and output data of the system to design the controller and gets rid of the dependence of the controller design on the model. However, this control method is difficult to control large delay and multi disturbance objects. In order to solve these problems, this paper proposes an anti disturbance model free adaptive controller based on Elman neural network prediction, which uses neural network to predict the system output, reduces the calculation amount of the algorithm, and speeds up the convergence speed; in addition, when solving the control variable, the disturbance factor is added to make the controller act in advance and improve the anti disturbance ability. This control method is applied to the coordinated control system of drum furnace, which shows the feasibility and effectiveness of this control method.

关键词： Neural networks Adaptation models control systems Data models Adaptive control Predictive models control theory

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Visual Coverage Maintenance for Quadcopters Using Nonsmooth Barrier Functions

Visual Coverage Maintenance for Quadcopters Using Nonsmooth ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Riku Funada María Santos Takuma Gencho Junya Yamauchi Masayuki Fujita Magnus Egerstedt Department of Aerospace Engineering and Engineering Mechanics The University of Texas Austin TX USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

This paper presents a coverage control algorithm for teams of quadcopters with downward facing visual sensors that prevents the appearance of coverage holes in-between the monitored areas while maximizing the coverage quality as much as possible. We derive necessary and sufficient conditions for preventing the appearance of holes in-between the fields of views among trios of robots. Because this condition can be expressed as logically combined constraints, control nonsmooth barrier functions are implemented to enforce it. An algorithm which extends control nonsmooth barrier functions to hybrid systems is implemented to manage the switching among barrier functions caused by the changes of the robots composing trio. The performance and validity of the proposed algorithm are evaluated in simulation as well as on a team of quadcopters.

关键词： Visualization Monitoring Robot sensing systems Switches Space missions

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Reliability Analysis of Conventional Island Water Supply System

Reliability Analysis of Conventional Island Water Supply Sys...

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International Conference on Mechanical, control and computer engineering (ICMCCE)

作者： YuTong Chai He Liu School of Control and Computer Engineering NCEPU Beijing China

ISBN: (数字)9781728146898

ISBN: (纸本)9781728146904

Go-flow method is an effective method to evaluate the reliability of complex systems with multi-timing characteristics, but at the same time, go-flow method has numerous operators and complex algorithms, which restricts the application of go-flow method in nuclear power reliability analysis. The reliability analysis method based on dynamic Bayesian network (DBN) is used to analyze the reliability of water supply system. Firstly, the mapping rules of go-flow operators to DBN nodes are defined. Then, according to the control logic and component characteristics of the water supply system, select the corresponding operator to establish the go-flow reliability model of the water supply system, and map the model to DBN model according to the corresponding rules. Finally, the mapped DBN model is quantitative solved. The sensitivity analysis (SA) of the model was carried out to obtain the influence degree of different components of the system. This method has the characteristics of high applicability, clear structure and fast computation.

关键词： Reliability Power system reliability Valves computer network reliability Bayes methods Computational modeling Analytical models

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Reliability Analysis of Solenoid Valve Power Supply Based on Time-Varying Fault Rate

Reliability Analysis of Solenoid Valve Power Supply Based on...

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International Conference on Mechanical, control and computer engineering (ICMCCE)

作者： He Liu Zicheng Wang Minglei Han School of Control and Computer Engineering NCEPU Beijing China

ISBN: (数字)9781728146898

ISBN: (纸本)9781728146904

Analyzing the structure of the solenoid valve power system and the failure mechanism of the solenoid valve system, a sampling method of the duration of the solenoid valve power state based on the time-varying failure rate is proposed, which provides a reference for the reliability analysis and improved design of the power system. First of all, reliability indicators are established, such as system reliability and average power loss time. And the time-varying failure rate is used to accurately reflect the aging process of the power system. In order to reflect the influence of failure rate with time accurately, the calculation of availability rate is improved. Secondly, analyzing the failure mode of the solenoid valve power system and the failure mechanism of the solenoid valve system. Finally, based on the failure mechanism of the solenoid valve power system, the sequential Monte Carlo method is used to simulate the real operation, and the correlation analysis is carried out according to the obtained results. The analysis results show that the proposed method improves the accuracy of reliability analysis and provides reference for power system analysis and improvement.

关键词： Reliability Solenoids Valves Power system reliability Circuit breakers Monte Carlo methods Maintenance engineering

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Collision-free Scheduling of Multi-bridge Machining Systems： A Colored Traveling Salesman Problem-based Approach

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 139-147页

作者： Jun Li Xianghu Meng Xing Dai Ministry of Education Key Laboratory of Measurement and Control School of Computer Science and Engineering Southeast University Nanjing 210096 China IEEE

Multi-bridge machining systems(MBMS) have gained wide applications in industry due to their high production capacity and efficiency. They contain multiple bridge machines working in parallel within their partially overlapping *** scheduling problems can be abstracted into a serial-colored travelling salesman problem in which each salesman has some exclusive cities and some cities shared with its neighbor(s). To solve it, we develop a greedy algorithm that selects a neighboring city satisfying proximity. The algorithm allows a salesman to select randomly its shared cities and runs accordingly many times. It can thus be used to solve job scheduling problems for MBMS. Subsequently, a collision-free scheduling method is proposed to address both job scheduling and collision resolution issues of MBMS. It is an extension of the greedy algorithm by introducing time window constraints and a collision resolution mechanism. Thus, the augmented greedy algorithm can try its best to select stepwise a job for an individual machine such that no time overlaps exist between it and the job sequence of the neighboring machine dealt in the corresponding overlapping workspace; and remove such a time overlap only when it is inevitable. Finally, we conduct a case study of a large triplebridge waterjet cutting system by applying the proposed method.

关键词： Collision resolution greedy algorithm modeling multiple traveling salesman problem scheduling

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