Dr. Hui Peng, Predictive control, Best Researcher Award

Doctorate at Central South University, China

Professional Profile

Scopus Profile


Hui Peng is a distinguished professor at Central South University’s School of Automation, with extensive experience in control engineering and statistical science. His prolific career includes over 70 publications and significant contributions to real industrial process control projects.


Hui Peng holds a robust academic background in control engineering and statistical science. He earned both his B.Eng. and M.Eng. degrees in Control Engineering from Central South University, Changsha, China, in 1983 and 1986, respectively. Furthering his expertise, he obtained his Ph.D. in Statistical Science from the Graduate University for Advanced Studies in Hayama, Japan, in 2003. His diverse educational journey has provided him with a solid foundation in both theoretical and applied aspects of control engineering and statistical analysis.

Professional Experience

Hui Peng has built a distinguished career in academia and industry. Since 1998, he has been a Professor in the School of Automation at Central South University in Changsha, China. His international experience includes serving as a Visiting Professor at the Institute of Statistical Mathematics in Tokyo, Japan, from 2000 to 2004 and again from 2009 to 2010. Since 2010, he has also been a Foreign Cooperative Professor at the Graduate University for Advanced Studies in Japan. Over his career, Hui Peng has authored more than 70 papers in international journals and co-invented a patent in Japan. He has successfully completed over ten real industrial process control projects, working with systems such as earth pressure balance shield machines, marine ships, cut tobacco dryers, thermal power plants, quadrotor helicopters, magnetic levitation systems, heat-treatment processes, and chemical reaction processes.

Research Interests

Hui Peng’s research interests lie at the intersection of control engineering and statistical science. His work focuses on nonlinear system modeling, statistical modeling, and system identification. He is also deeply involved in nonlinear optimization and signal processing, exploring advanced techniques to enhance predictive and robust control systems. His expertise extends to process control, where he applies his knowledge to improve the efficiency and reliability of industrial processes. Additionally, Hui Peng is interested in financial process modeling and portfolio optimization, aiming to develop sophisticated models for better financial decision-making and risk management.

đź“– Publication Top Noted

Deep learning based model predictive controller on a magnetic levitation ball system

    • Authors: Peng, T., Peng, H., Li, R.
    • Journal: ISA Transactions
    • Volume: 149
    • Pages: 348–364
    • Year: 2024

Parameter Optimization of Steam Generator Water Level Control System Based on Piecewise ARX Modeling

    • Authors: Liu, F., Jiang, Y., Li, Y., Wang, J., Peng, T.
    • Journal: IEEE Transactions on Nuclear Science
    • Volume: 71
    • Issue: 2
    • Pages: 135–153
    • Year: 2024

A novel nonlinear model predictive control strategy and its application to maglev ball system

    • Authors: Peng, T., Li, H., Peng, H., Qin, Y., Peng, X.
    • Journal: International Journal of Control
    • Year: 2024

Machine vision-based online detection method for color characteristics of cobalt extraction solution

    • Authors: Zhang, H., Qu, Y., Peng, H., Peng, T., Tian, B.
    • Journal: Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering
    • Year: 2024

RBF-ARX model-based MPC approach to inverted pendulum: An event-triggered mechanism

    • Authors: Tian, B., Peng, H.
    • Journal: Chaos, Solitons and Fractals
    • Volume: 176
    • Page: 114081
    • Year: 2023

LSTM-CNN Network-Based State-Dependent ARX Modeling and Predictive Control with Application to Water Tank System

    • Authors: Kang, T., Peng, H., Peng, X.
    • Journal: Actuators
    • Volume: 12
    • Issue: 7
    • Page: 274
    • Year: 2023
Hui Peng | Predictive control | Best Researcher Award

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