电子邮箱:

sdzzhn@zzu.edu.cn

办公室:

郑州大学电气与信息工程学院3108

研究方向:

人-机器人交互、机器人柔顺控制、神经网络控制.

教育背景

2017/09-2023/12，郑州大学，电气与信息工程学院，博士

2013/09-2017/06，郑州大学，电气工程学院，学士

工作经历

Ø  2024/04-至今，郑州大学，电气与信息工程学院，副研究员（直聘）

学术兼职

Ø  担任IEEE   Transactions on Industrial Electronics、IEEE Transactions on Automation Science   and Engineering等期刊审稿人

奖励与荣誉

Ø  2023年，郑州大学电气与信息工程学院学术之星

Ø  2022年，博士研究生国家奖学金

Ø  2022年，河南省教育厅科技成果奖优秀科技论文奖-壹等

Ø  2020、2021年，郑州大学研究生优秀成果奖

科研项目

Ø  （参与）国家自然科学基金面上项目（62273311），2023.01-2026.12

Ø  （参与）国家自然科学基金面上项目（61773351），2018.01-2021.12

代表文章

[1]   Shuai Ding, Jinzhu Peng, JianbinXin, Hui Zhang, Yaonan Wang.   Task-oriented adaptive position/force control for robotic systems under   hybrid constraints. IEEE Transactions on Industrial Electronics, 2024, 71(10):   12612-12622. (中科院1区)

[2]   Shuai Ding, Jinzhu Peng, Hui Zhang, Yaonan Wang. Event-triggered   adaptive neural impedance control of robotic systems. IEEE Transactions on   Neural Networks and Learning Systems, 2024, 35(10): 14330-14340. (中科院1区)

[3]   Shuai Ding, Jinzhu Peng, JianbinXin, Hui Zhang, Yaonan Wang.   Vision-based virtual impedance control for robotic system without   prespecified task trajectory. IEEE Transactions on Industrial Electronics,   2023, 70(6): 6046-6056. (中科院1区)

[4]   Jinzhu Peng, Shuai Ding, Zeqi Yang, Jianbin Xin. Adaptive neural   impedance control for electrically driven robotic systems based on a   neuro-adaptive observer. Nonlinear Dynamics, 2020, 100: 1359-1378. (中科院1区)

[5]   Jinzhu Peng, Shuai Ding, Rickey Dubay. Adaptive composite neural   network disturbance observer-based dynamic surface control for electrically   driven robotic manipulators. Neural Computing & Applications, 2021,   33(11): 6197-6211. (中科院2区)

[6]   Shuai Ding, Jinzhu Peng, Hui Zhang, Yaonan Wang. Neural network-based   adaptive hybrid impedance control for electrically driven flexible-joint   robotic manipulators with input saturation. Neurocomputing, 2021, 458:   99-111. (中科院2区)

[7]   Jinzhu Peng, Shuai Ding, Zeqi Yang, Fangfang Zhang. Neural   network-based hybrid position/force tracking control for robotic systems   without velocity measurement. Neural Processing Letters, 2020, 51(2):   1125-1144. (中科院3区)

[8]   Shuai Ding, Jinzhu Peng, Yan Liu, Yage Wu. Neural adaptive control for   robotic systems with saturation and disturbance. 2023 8th International   Conference on Automation, Control and Robotics Engineering, Hong Kong, China,   2023, 242-247. (EI会议)

[9]   Shuai Ding, Jinzhu Peng, Wang Zhiqiang, Mengchao Dong. Observer-based   adaptive impedance control for robotic systems with predefined task space.   2021 China Automation Congress, Beijing, China, 2021, 1161-1166. (EI会议)

[10]   Shuai Ding, Jinzhu Peng, Yixin Hou, Xiaodong Lei. Neural network-based   hybrid position/force tracking control for flexible joint robot. 2020 IEEE   International Systems Conference, Montreal, QC, Canada, 2020, 1-6. (EI会议)

[11]   Jinzhu Peng, Shuai Ding, Rickey Dubay. Adaptive impedance control   based on neural network for electrically-driven robotic systems. 2020 IEEE   International Systems Conference, Montreal, QC, Canada, 2020, 1-6. (EI会议)

其他信息

Ø  无。