Dong Liu | Data Driven Control | Best Researcher Award

Prof. Dong Liu | Data Driven Control | Best Researcher Award

Deputy Director of Provincial Key Laboratory at Shenyang Aerospace University, China

Dong Liu is an Associate Professor at the College of Automation, Shenyang Aerospace University, China. He is a leading researcher in the field of control theory and engineering, especially recognized for his work on data-driven control, model-free adaptive control, and secure control systems. He plays active roles in various national technical committees related to automation, command and control, and artificial intelligence.

Publication ProfileΒ 

Scopus

Orcid

Educational Background πŸŽ“

  • Ph.D. in Control Theory and Control Engineering,
    Northeastern University, China β€” 2018

Professional Experience πŸ’Ό

  • Associate Professor,
    College of Automation, Shenyang Aerospace University

  • Deputy Director,
    Liaoning Provincial Key Laboratory of Advanced Flight Control and Simulation Technology

  • Recognized as a High-Level Talent by Shenyang Municipality

Committee Roles:

  • Committee Member, Technical Committee on Data-Driven Control, Learning, and Optimization (Chinese Association of Automation)

  • Committee Member, Technical Committee on Intelligent Control and Systems (Chinese Command and Control Association)

  • Committee Member, Technical Committee on Intelligent Detection and Motion Control Technology (Chinese Association for Artificial Intelligence)

Research Interests πŸ”¬

  • Data-Driven Control

  • Model-Free Adaptive Control (MFAC)

  • Secure Control Systems

  • Sliding Mode Control

  • Cyber-Physical Systems

  • Prescribed Performance Control

  • Aerospace Control Applications

  • Event-Triggered and Reinforcement Learning-based Control

Awards and HonorsπŸ†βœ¨

  • Recognized as High-Level Talent by the Shenyang Municipality

  • Appointed Deputy Director of a Provincial Key Laboratory

  • Holds Multiple Technical Committee Memberships in prestigious national associations

Conclusion🌟

Dr. Dong Liu is an influential scholar in control engineering, especially in data-driven and model-free adaptive control systems with an emphasis on robustness, security, and real-time applications in aerospace and cyber-physical systems. His high-impact journal publications and leadership roles in national technical committees underline his strong academic and technical contributions. He is actively shaping the future of intelligent control in China and internationally.

Publications πŸ“š

πŸ“˜ Data-driven second-order iterative sliding mode control for cyber–physical systems under prescribed performance and DoS attacks
✍️ Yijie Yang, Dong Liu, Xin Wang, Zhujun Wang
πŸ—žοΈ Journal of Process Control, June 2025
πŸ”— DOI: 10.1016/j.jprocont.2025.103422


πŸ“˜ Prescribed performance based data-driven adaptive sliding mode control for discrete-time nonlinear systems
✍️ Dong Liu, Yi-Jie Yang, Li-Ying Hao
πŸ—žοΈ Journal of the Franklin Institute, March 2024
πŸ”— DOI: 10.1016/j.jfranklin.2024.01.021


πŸ“˜ Data-Driven Bipartite Consensus Tracking for Nonlinear Multiagent Systems With Prescribed Performance
✍️ Dong Liu, Zhi-Peng Zhou, Tie-Shan Li
πŸ—žοΈ IEEE Trans. on Systems, Man, and Cybernetics: Systems, 2023
πŸ”— DOI: 10.1109/TSMC.2022.3230504


πŸ“˜ Event‐triggered model‐free adaptive control for nonlinear systems with output saturation
✍️ Dong Liu, Ning Liu, Tieshan Li
πŸ—žοΈ Int. Journal of Robust and Nonlinear Control, August 2023
πŸ”— DOI: 10.1002/rnc.6747


πŸ“˜ Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance
✍️ Dong Liu, Guang-Hong Yang
πŸ—žοΈ IEEE Trans. on Systems, Man, and Cybernetics: Systems, December 2019
πŸ”— DOI: 10.1109/TSMC.2017.2779564


πŸ“˜ Prescribed Performance Model-Free Adaptive Integral Sliding Mode Control for Discrete-Time Nonlinear Systems
✍️ Dong Liu, Guang-Hong Yang
πŸ—žοΈ IEEE Trans. on Neural Networks and Learning Systems, July 2019
πŸ”— DOI: 10.1109/TNNLS.2018.2881205


πŸ“˜ Model-Free Adaptive Control Design for Nonlinear Discrete-time Processes with Reinforcement Learning Techniques
✍️ Dong Liu
πŸ—žοΈ International Journal of Systems Science, July 2018
πŸ”— [Link not provided]


πŸ“˜ Performance-based data-driven model-free adaptive sliding mode control for a class of discrete-time nonlinear processes
✍️ Dong Liu
πŸ—žοΈ Journal of Process Control, June 2018
πŸ”— [Link not provided]


πŸ“˜ Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance
✍️ Dong Liu
πŸ—žοΈ IEEE Trans. on Systems, Man, and Cybernetics: Systems, November 2017
πŸ”— [Link not provided]


πŸ“˜ Event-based model-free adaptive control for discrete-time non-linear processes
✍️ Dong Liu
πŸ—žοΈ IET Control Theory & Applications, September 2017
πŸ”— [Link not provided]


πŸ“˜ Neural network-based event-triggered MFAC for nonlinear discrete-time processes
✍️ Dong Liu
πŸ—žοΈ Neurocomputing, July 2017
πŸ”— [Link not provided]


Zhiyang Guo | Sliding Mode Control | Best Scholar Award

Dr. Zhiyang Guo | Sliding Mode Control | Best Scholar Award

Doctoral Candidate at Dalian Maritime University, China

🌊 Dr. Zhiyang Guo is a passionate researcher in maritime engineering and control systems, currently pursuing a Ph.D. at Dalian Maritime University. With expertise in sliding mode control and autonomous vehicles, he has published impactful research articles and holds patents in innovative maritime technologies. πŸš€πŸ”¬ His work contributes to advancing the capabilities of unmanned and autonomous surface vehicles, driving innovation in the maritime industry. 🌟

Publication Profile :Β 

Scopus

Educational Background πŸŽ“

Zhiyang Guo is currently a Doctoral Candidate at Dalian Maritime University, where he has been pursuing his Ph.D. since 2022. He previously completed his Master’s degree at the same institution from 2020 to 2022, specializing in cutting-edge maritime technologies.

Professional Experience πŸ’Ό

Zhiyang Guo has demonstrated a strong commitment to advancing maritime engineering and control systems. His research focuses on unmanned surface vehicles (USVs) and autonomous surface vehicles (ASVs), particularly in sliding mode control. He has contributed to the field through patent applications and publications in esteemed journals, showcasing his innovative approach to maritime maneuverability and control systems.

Research Interests πŸ”¬

  • Sliding mode control
  • Unmanned surface vehicles (USVs)
  • Autonomous surface vehicles (ASVs)

Achievements and Innovations

Zhiyang has filed two patents (Application Numbers: 202410936299.5 and 202410936301.9) and authored influential journal articles, including:

  1. Turning and zigzag maneuverability investigations on a waterjet-propelled trimaran in calm and wavy water using a direct CFD approach (DOI: 10.1016/j.oceaneng.2023.115511)
  2. Predefined-time global recursive sliding mode control for trajectory tracking of unmanned surface vehicles with disturbances uncertainties (DOI: 10.1016/j.oceaneng.2024.119408)

Publications πŸ“š

  • Guo, Z., Zhang, J., Shang, Y., Zhang, L., & Chen, W. (2024). Predefined-time global recursive sliding mode control for trajectory tracking of unmanned surface vehicles with disturbances uncertainties. Ocean Engineering, 313, 119408.

  • Zhang, J., Guo, Z., Zhang, Q., Shang, Y., & Zhang, L. (2023). Turning and zigzag maneuverability investigations on a waterjet-propelled trimaran in calm and wavy water using a direct CFD approach. Ocean Engineering, 286, 115511.

  • Cui, Y., Wang, D., Guo, Z., Zhang, L., & Zhang, J. (2023). Maneuverability prediction for trimaran ship under the combined influence of wind and wave. Proceedings of SPIE – The International Society for Optical Engineering, 12756, 127564V.

  • Wei, Y., Zhang, J., Guo, Z., Shang, Y., & Zhang, L. (2023). Research on added waves resistance in misalignment paralleling of two ships. Proceedings of SPIE – The International Society for Optical Engineering, 12756, 127561G.