Wang David

Professor   Supervisor of Doctorate Candidates   Supervisor of Master's Candidates

Gender:Male

Alma Mater:Dalian University of Technology

Degree:Doctoral Degree

School/Department:School of Control Science and Engineering

Discipline:Control Theory and Control Engineering. Pattern Recognition and Intelligence System. Navigation, Guidance and Control

Business Address:Rm A628, Haishan BLDG

Contact Information:dwang[@]dlut.edu.cn


Paper Publications

Distributed Extremum Seeking for Optimal Resource Allocation and Its Application to Economic Dispatch in Smart Grids

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Indexed by:Journal Papers

Date of Publication:2019-10-01

Journal:IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

Included Journals:SCIE

Volume:30

Issue:10

Page Number:3161-3171

ISSN No.:2162-237X

Key Words:Distributed optimization; economic dispatch; extremum-seeking; multiagent system; resource allocation

Abstract:This paper proposes a first-order extremum-seeking algorithm to solve the resource allocation problem, where the specific expression form and gradient information of the local cost functions are not required. Agents take advantage of measurements of local cost functions to minimize the sum of their cost functions while satisfying the resource constraint, where agents exchange the estimated decisions with their neighbors under an undirected and connected graph. Making use of the Lyapunov stability theory and the average analysis method, the convergence of the proposed algorithm to the neighborhood of the optimal solution is presented. In addition, it is obtained that the designed algorithm is semiglobally practically asymptotically stable. Then, the first-order algorithm is extended to the second-order algorithm with low-pass filters, which achieves better convergence performance than the first-order algorithm. Finally, the effectiveness of the proposed algorithm is illustrated by numerical examples and its application to economic dispatch in smart grids.

Pre One:Multi-Robot Formation and Tracking Control Method

Next One:An event-triggered protocol for distributed optimal coordination of double-integrator multi-agent systems

Profile

王东,控制科学与工程学院教授,博士生导师,国家级人才特聘教授,科技部重点研发计划项目首席科学家,智能控制研究所所长,控制科学与工程博士学位授权点点长。


主要从事多智能体分布式控制与优化、基于强化学习的博弈对抗、多机器人协同控制等研究工作。在世界知名学术出版社Springer出版英文专著1部,在控制领域顶级期刊Automatica和IEEE trans Automatic Control等国内外核心期刊、会议发表和录用论文120余篇,其中,SCI检索和刊源80余篇,Google学术总引用3000余次,申请和授权发明专利10余项,授权软件著作权7项。


第一完成人获得辽宁省科技奖励自然科学二等奖,第七届吴文俊人工智能科技奖励自然科学二等奖。荣获中国控制会议关肇直优秀论文提名奖,全国百篇优秀博士学位论文提名奖,辽宁省优秀博士学位论文。


主持多项无人机集群、多机器人协同控制和强化学习的博士对抗项目,典型的包括国家重点研发计划项目、国家自然科学基金重点项目,1*3基础加强计划项目,装发预研教育部联合基金、国家自然科学基金面上项目、青年基金项目等,参与多项国家级项目。是国家自然科学基金,中国博士后科学基金,波兰科学基金等项目和国家级人才评选的通讯评审专家。


实验室有多旋翼无人机、单臂移动机器人,双臂协作机器人和多种地面无人移动平台等设备。可供研究生开展各种试验和科学研究。


担任国际知名SCI检索期刊《Information Sciences》、《Neurocomputing》等副编, 国内核心期刊《控制理论与应用》,《智能系统学报》等编委,中国控制会议程序委员会委员。担任中国指挥与控制学会青年工作委员会副主任,中国自动化学会控制理论专业委员会委员(TCCT Member),中国自动化学会信息物理系统专业委员会委员(TCPS Member),IEEE 高级会员。


曾访问美国圣母大学和波士顿大学,新加坡南洋理工大学、日本芝浦工业大学、英国埃塞克斯大学等长期访问,美国斯坦福大学、加州大学尔湾分校等短期合作交流。


所指导的研究生获国家奖,省优秀毕业生,市优秀毕业生,校优秀毕业生,校优秀毕业学位论文等荣誉,并到华为、中兴等单位工作。指导的博士研究生获得辽宁省优秀博士学位论文和中国指挥与控制学会(CICC)“博士学位论文激励计划”(中国指挥与控制学会优秀博士论文)等荣誉称号。