姓名: Dr Shuai Li
职务: 机器人运动学与编程课程负责人
网页: Dr Shuai Li - Swansea University
简介:
李先生（Steven）现任理工学院副教授。他的主要研究兴趣包括人工智能、机器学习、控制算法、机器人、非线性优化和控制。他在同行评审期刊上发表200多篇SCI索引期刊论文（包括90多篇IEEE）。
教育背景:
美国史蒂文斯理工学院电气与计算机工程博士
中国科学技术大学电气工程硕士
工作经历:
2019-至今 副教授 斯旺西大学
研究方向:
机器人
神经网络
非线性优化与控制
高级算法
制造自动化
代表性成果:
1. Guo, D., Li, S., & Stanimirovic, P. (2020). Analysis and Application of Modified ZNN Design With Robustness Against Harmonic Noise. IEEE Transactions on Industrial Informatics, 16(7), 4627-4638. https://doi.org/10.1109/tii.2019.2944517, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52457
2. Chen, D., Li, S., Wu, Q., & Luo, X. (2019). Super-twisting ZNN for coordinated motion control of multiple robot manipulators with external disturbances suppression. Neurocomputing. https://doi.org/10.1016/j.neucom.2019.08.085, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52014
3. Chen, D., Li, S., Li, W., & Wu, Q. (2019). A Multi-Level Simultaneous Minimization Scheme Applied to Jerk-Bounded Redundant Robot Manipulators. IEEE Transactions on Automation Science and Engineering, 1-12. https://doi.org/10.1109/TASE.2019.2931810, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51998
4. Xu, Z., Zhou, X., & Li, S. (2019). Deep Recurrent Neural Networks Based Obstacle Avoidance Control for Redundant Manipulators. Frontiers in Neurorobotics, 13. https://doi.org/10.3389/fnbot.2019.00047, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52000
5. Chen, D., Li, S., & Wu, Q. (2019). A Novel Disturbance Rejection Zeroing Neurodynamic Approach for Robust Synchronization of Chaotic Systems. IEEE Access, 7, 121184-121198. https://doi.org/10.1109/ACCESS.2019.2938016, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52006
6. Mao, C., Li, S., Chen, Z., Zu, H., Wang, Z., & Wang, Y. (2019). A Novel Algorithm for Robust Calibration of Kinematic Manipulators and its Experimental Validation. IEEE Access, 7, 90487-90496. https://doi.org/10.1109/access.2019.2926801, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52004
7. Chen, D., Li, S., Lin, F., & Wu, Q. (2020). New Super-Twisting Zeroing Neural-Dynamics Model for Tracking Control of Parallel Robots: A Finite-Time and Robust Solution. IEEE Transactions on Cybernetics, 1-10. https://doi.org/10.1109/TCYB.2019.2930662, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52001
8. Khan, A., Li, S., & Luo, X. (2020). Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach. IEEE Transactions on Industrial Informatics, 16(7), 4670-4680. https://doi.org/10.1109/tii.2019.2941916, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa51997 http://dx.doi.org/10.1109/tii.2019.2941916
9. Zhou, X., Xu, Z., & Li, S. (2019). Collision-Free Compliance Control for Redundant Manipulators: An Optimization Case. Frontiers in Neurorobotics, 13. https://doi.org/10.3389/fnbot.2019.00050, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52009
10. Chen, D., Li, S., & Liao, L. (2019). A recurrent neural network applied to optimal motion control of mobile robots with physical constraints. Applied Soft Computing, 85, 105880. https://doi.org/10.1016/j.asoc.2019.105880, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa52559
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