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Culture versus Policy: More Global Collaboration to Effectively Combat COVID-19

The Innovation 2020年第2期1卷 15-16页

作者： Jianping Li Kun Guo Enrique Herrera Viedma Heesoek Lee Jiming Liu Ning Zhong Luiz Flavio Autran Monteiro Gomes Florin Gheorghe Filip Shu-Cherng Fang Mujgan SagirÖzdemir Xiaohui Liu Guoqing Lu Yong Shi School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Chinese Academy of SciencesBeijing 100190China Department of Computer Science and Artificial Intelligence E.T.S.de Ingenieria Informatica y de TelecomunicacionesUniversity of Granada18071 GranadaSpain Department of Information Management Korea Advanced Institute of Science and TechnologySeoul 207-43 Korea Department of Computer Science and HKBU-CSD&NIPD Joint Research Laboratory for Intelligent Disease Surveillance and Control Hong Kong Baptist UniversityHong KongChina Department of Life Science and Informatics Maebashi Institute of TechnologyMaebashi 371-0816Japan Ibmec University Center Av.Presidente Wilson118Office#111020030-020 Rio de JaneiroBrazil The Romanian Academy Bucharest010071Romania Industrial and Systems Engineering Department North Carolina State UniversityRaleighNC 27695USA Department of Industrial Engineering Eskisehir Osmangazi University26480 EskisehirTurkey Department of Computer Science Brunel University LondonLondonUB83PHUK Department of Biology and School of Interdisciplinary Informatics University of Nebraska at OmahaOmahaNE 68182USA College of Information Science and Technology University of Nebraska at OmahaOmahaNE 68182USA

The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic *** and anti-epidemic policy do not necessarily conflict with each *** countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.

关键词： seeking overcome policy

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Finite-sample analysis of decentralized temporal-difference learning with linear function Approximation

arXiv

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arXiv 2019年

作者： Sun, Jun Wang, Gang Giannakis, Georgios B. Yang, Qinmin Yang, Zaiyue College of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China

Motivated by the emerging use of multi-agent reinforcement learning (MARL) in engineering applications such as networked robotics, swarming drones, and sensor networks, we investigate the policy evaluation problem in a fully decentralized setting, using temporal-difference (TD) learning with linear function approximation to handle large state spaces in practice. The goal of a group of agents is to collaboratively learn the value function of a given policy from locally private rewards observed in a shared environment, through exchanging local estimates with neighbors. Despite their simplicity and widespread use, our theoretical understanding of such decentralized TD learning algorithms remains limited. Existing results were obtained based on i.i.d. data samples, or by imposing an ‘additional’ projection step to control the ‘gradient’ bias incurred by the Markovian observations. In this paper, we provide a finite-sample analysis of the fully decentralized TD(0) learning under both i.i.d. as well as Markovian samples, and prove that all local estimates converge linearly to a small neighborhood of the optimum. The resultant error bounds are the first of its type—in the sense that they hold under the most practical assumptions —which is made possible by means of a novel multi-step Lyapunov analysis. Copyright © 2019, The Authors. All rights reserved.

关键词： Sampling

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Event-triggered optimal containment control for heterogeneous multi-agent systems

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Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica 2020年 41卷

作者： Wang, Dong Wang, Zehua Liu, Yang Gu, Dongbing Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Eduction Dalian University of Technology Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park ColchesterCO4 3SQ United Kingdom

An edge-based event-triggered optimal control algorithm is proposed to solve the optimal output containment problem of general linear heterogeneous multi-agent systems. The proposed algorithm guarantees that the outputs of all followers enter into the convex hull formed by the outputs of leaders. At the same time, it can also render that the closed-loop system achieves the optimal performance and minimize the cost of control. Considering that the information of the leaders is unavailable to a part of followers, a distributed edge-based event-triggered observer is presented to estimate the trajectory for the interior point in the convex hull. In addition, a weighted performance function is designed to transform the output containment problem into the optimal state-feedback design problem. Based on the proposed function, the Bellman equation and algebraic Riccati equation are derived to solve the optimal output containment control problem of heterogeneous multi-agent systems. Multiple autonomous robots are employed as a group of multi-agent systems to verify the effectiveness of the proposed algorithm. © 2020, Beihang University Aerospace Knowledge Press. All right reserved.

关键词： Multi agent systems

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A Robust and Efficient Algorithm for Coprime Array Adaptive Beamforming

A Robust and Efficient Algorithm for Coprime Array Adaptive ...

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作者： Zhou, Chengwei Gu, Yujie He, Shibo Shi, Zhiguo College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Temple University PhiladelphiaPA19122 United States State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou Zhejiang University 310027 China

Coprime array offers a larger array aperture than uniform linear array with the same number of physical sensors, and has a better spatial resolution with increased degrees of freedom. However, when it comes to the problem of adaptive beamforming, the existing adaptive beamforming algorithms designed for the general array cannot take full advantage of coprime feature offered by the coprime array. In this paper, we propose a novel coprime array adaptive beamforming algorithm, where both robustness and efficiency are well balanced. Specifically, we first decompose the coprime array into a pair of sparse uniform linear subarrays and process their received signals separately. According to the property of coprime integers, the direction-of-arrival (DOA) can be uniquely estimated for each source by matching the super-resolution spatial spectra of the pair of sparse uniform linear subarrays. Further, a joint covariance matrix optimization problem is formulated to estimate the power of each source. The estimated DOAs and their corresponding power are utilized to reconstruct the interference-plus-noise covariance matrix and estimate the signal steering vector. Theoretical analyses are presented in terms of robustness and efficiency, and simulation results demonstrate the effectiveness of the proposed coprime array adaptive beamforming algorithm. © 1967-2012 IEEE.

关键词： Covariance matrix

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Adaptive Dual Model Differential Evolution Algorithm Based on Cloud Model

Adaptive Dual Model Differential Evolution Algorithm Based o...

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第30届中国控制与决策会议

作者： Hu Zhongquan Zhou Zhen Wang Hongbin Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

To solve the problem of premature convergence and search stagnation in traditional differential algorithm, this paper presents an adaptive dual model differential evolution algorithm based on cloud model(ADDEC). The variation model of ADDEC is produced by combining basic variation with cloud variation. And the adaptive operators are referenced respectively for scale factor and interactive probability during the operation of variation and crossover. The robustness and the convergence rate of the algorithm are enhanced. Moreover the relationship between global search and local search of the algorithm is improved. The diversity of the population is guaranteed at the same time. It is tested by typical high dimension benchmark function and compared with other algorithms, and the results show that the ADDEC has better precision, high convergence speed and makes it easy to jump out the local optimal solution.

关键词： Differential evolution algorithm Cloud model Evolution strategy Adaptive

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Dynamic Event-Triggered Formation control for Multiple Quadrotor UAVs

Dynamic Event-Triggered Formation Control for Multiple Quadr...

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第37届中国控制会议

作者： WANG Hongbin ZHOU Zhen WANG Yueling ZHANG Mingquan XUE Xiaojun Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

This paper deals with the formation control problem for a group of quadrotor unmanned aerial vehicles（UAVs） through a modified dynamic event-triggered control protocol. The stability proof for the state space origin of the overall closed-loop system is derived from the singular perturbation method and Lyapunov stability theory. An event-triggered formation control protocol in terms of a dynamically varying threshold parameter is delicately carried out while acquiring satisfactory resource efficiency, and Zeno behavior of triggering time sequences is excluded. Finally, simulations on four quadrotor UAVs are given to verify the effectiveness of the theoretical results.

关键词： Formation control Singular perturbation Dynamic event-triggered controller Multiple quadrotor UAVs

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Guidance Vector Field Encoding based on Contraction Analysis 16

Guidance Vector Field Encoding based on Contraction Analysis

引用

16th European control Conference, ECC 2018

作者： Wu, Chengshuai Chen, Jian Jeltsema, DImitri Dai, And Chenxi State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Section Control Systems Engineering HAN University of Applied Science P.O. Box 2217 Arnhem6802 CE Netherlands Department of Electrical and Computer Engineering Ohio State University Columbus43210 United States

ISBN: (纸本)9783952426982

The guidance vector field encoding problem is revisited via exploiting the recently developed differential Lyapunov framework for contraction analysis. In control applications, a designed guidance vector field is utilized to guide a particle (such as a robot, or an end actuator) to converge to and circulate along a target curve, such as robot navigation, or motion planing. This paper proposes some new methods for guidance vector filed encoding. The methods analyze the guidance vector field encoding problem from a theoretical perspective providing insights into the problem, and it shows that the contraction analysis is a natural theoretical tool for guidance vector encoding. Furthermore, the differences and relations between the proposed result and the previous methods are discussed. Simulation examples are presented to illustrate the effectiveness of the proposed methods. © 2018 European control Association (EUCA).

关键词： Robots

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Analysis of moving target defense against false data injection attacks on power grid

arXiv

引用

arXiv 2019年

作者： Zhang, Zhenyong Deng, Ruilong Yau, David K.Y. Cheng, Peng Chen, Jiming State Key Laboratory of Industrial Control Technology College of Control Science and Engi-neering Zhejiang University Hangzhou310027 China School of Computer Science and Engineering Nanyang Technological University 639798 Singapore Information Systems Technology and Design Singapore University of Technology and Design 487372 Singapore

Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker to launch stealthy FDI attacks generated with former branch susceptances. In this paper, we prove that, an MTD has the capability to thwart all FDI attacks constructed with former branch susceptances only if (i) the number of branches l in the power system is not less than twice that of the system states n (i.e., l ≥ 2n, where n + 1 is the number of buses);(ii) the susceptances of more than n branches, which cover all buses, are perturbed. Moreover, we prove that the state variable of a bus that is only connected by a single branch (no matter it is perturbed or not) can always be modified by the attacker. Nevertheless, in order to reduce the attack opportunities of potential attackers, we first exploit the impact of the susceptance perturbation magnitude on the dimension of the stealthy attack space, in which the attack vector is constructed with former branch susceptances. Then, we propose that, by perturbing an appropriate set of branches, we can minimize the dimension of the stealthy attack space and maximize the number of covered buses. Besides, we consider the increasing operation cost caused by the activation of MTD. Finally, we conduct extensive simulations to illustrate our findings with IEEE standard test power systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Network security

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Fuzzy Q-learning obstacle avoidance algorithm of humanoid robot in unknown environment 37

Fuzzy Q-learning obstacle avoidance algorithm of humanoid ro...

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37th Chinese control Conference, CCC 2018

作者： Wen, Shuhuan Chen, Jianhua Li, Zhen Rad, Ahmad B. Mohammed Othman, Kamal Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China School of Engineering Sciences Simon Fraser University SurreyBCV3T 0A3 Canada

ISBN: (纸本)9789881563941

This paper proposes a fuzzy Q-learning (FQL) algorithm to solve the problem of the robot obstacle avoidance in unknown environment. FastSLAM algorithm is used to localize the position of the robot. Traditional Q-learning algorithm, optimized Q-learning algorithm, FQL algorithm are compared. The simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective. © 2018 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Anthropomorphic robots

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Sensor Fault Detection of Continuous Casting Mold Vibration System Driven by Servo Motor

Sensor Fault Detection of Continuous Casting Mold Vibration ...

引用

Chinese control Conference (CCC)

作者： Xia Wu Jianxiong Li Yiming Fang Zhiqiang Wang Key Lab of Industrial Computer Control Engineering of Yanshan University Qinhuangdao Hebei Province China

The problem of sensor fault diagnosis and reconstruction of the continuous casting mold vibration displacement system driven by servo motor is investigated in this paper, and a fault reconstruction method based on adaptive sliding mode observer is proposed. Firstly, the matching condition of the observer is satisfied by constructing an auxiliary output, and a new state variable is selected as the low-pass filter with the fault vector output. Then an adaptive sliding mode observer is designed for the auxiliary output system in the present of the unknown upper bound of the fault, in which the adaptive switching gain is updated online. The gain matrix of the observer is obtained by solving a LMI optimization problem. And a linear transforming matrix is introduced to realize the direct estimation of the fault by the principle of the equivalent control output error injection. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

关键词： Observers Casting Mathematical model Servomotors Adaptive systems Vibrations Upper bound

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