Yue Ming

Personal Information

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Professor   Supervisor of Doctorate Candidates   Supervisor of Master's Candidates  

Profile

Yue Ming, Ph.D, Full Professor.

 

Focusing on complex transport equipment such as intelligent vehicles and mobile robots, he devotes to the research on intelligent system synthesis, trajectory planning methods, and control system design, oriented to improve the high-performance motion performances of sophisticated vehicle/robot systems.

 

In recent years, he has been selected as a fixed member of "Liaoning Provincial College Innovation Talent Program" and "State Key Laboratory of Industrial Equipment Structure Analysis". He has been awarded the title of Excellent Master's thesis advisor in Liaoning Province. He has published more than 100 academic papers, among which more than 60 were indexed by SCI database. It has obtained more than 40 authorized invention patents.

 

As the project leader, he was obtained more than 10 national projects, and nearly 20 other provincial and ministerial projects. He is a member of IEEE, ASME and Automation Society. He is also a member of China Association of Automobile Manufacturers' group Standard expert database, a member of China Association of Automation—Vehicle Control and Intelligence Special Committee, and a member of China Association of Automation—Parallel Intelligence Committee.


Educational ExperienceMore>>

2004.9 2008.5

  • 哈尔滨工业大学
  • 机械设计及理论
  • Doctoral Degree

2002.9 2004.7

  • 哈尔滨工业大学
  • 机械设计及理论
  • Master's Degree

1994.9 1998.7

  • 郑州大学
  • 机械设计及制造
  • Bachelor's Degree

Work Experience

2008.7 2011.12
  • 大连理工大学汽车工程学院
  • 讲师
1998.8 2002.7
  • 宁波中策动力机电集团公司
  • 助理工程师

Social AffiliationsMore>>

2018.1 2018.12

  • 机器人分会委员会委员(中国机械工程学会)

2020.1 2020.12

  • 委员(中国自动化学会车辆控制与智能化专委会)

2018.1 2018.12

  • 平行智能委员会委员(中国自动化学会)

Research Focus

  • 欢迎勤奋好学的车辆、机械、控制等专业同学报考硕士及博士研究生,招收博士后。主要领域和方向如下: 

    (1) 智能车辆 

          面向极端复杂工况,研究拖挂、重载等特种车辆状态观测、运动规划与稳定性控制等基础理论与关键技术。 

    (2) 机器人动力学与控制 

          针对拖挂机器人、两轮车、机械臂等机器人系统,开展构型综合、动力学分析、协调避障研究。

    (3) 先进控制理论与应用 

         综合运用滑模变结构、模型预测、神经/模糊等先进控制理论,开展复杂机电耦合系统高性能运动控制研究。