Qixun Lan | Nonlinear Control | Best Researcher Award

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Assoc. Prof. Dr. Qixun Lan | Nonlinear Control | Best Researcher Award

Assoc. Prof. Dr. Qixun Lan, Zhengzhou University of Light Industry, China

Assoc. Prof. Dr. Qixun Lan is an Associate Professor and Master’s Supervisor at the School of Electrical and Information Engineering, Zhengzhou University of Light Industry. He holds a B.S. in Information and Computing Science from Henan Normal University (2005), an M.S. in Operations Research and Control Theory from Guangxi University (2008), and a Ph.D. in Control Science and Engineering from Southeast University (2016). Dr. Lan has conducted international research as a visiting scholar at the University of Texas at San Antonio (2014–2015) and Loughborough University, UK (2024–2025). His research interests include nonsmooth control of nonlinear systems, disturbance estimation and suppression, advanced control for aircraft systems, and high-performance servo systems. He has led projects funded by the National Natural Science Foundation and various provincial and municipal agencies. With over 40 academic publications, including 30+ SCI/EI-indexed papers, he has received four Henan Provincial Outstanding Scientific and Technological Achievement Awards and actively serves on the Discontinuous Control Technical Committee of the Chinese Association of Automation.

Publication Profile

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🎓 Academic Background & International Exposure

Assoc. Prof. Dr. Qixun Lan has built a strong academic foundation with degrees spanning key areas of engineering and applied mathematics. He earned his B.S. in Information and Computing Science from Henan Normal University in 2005, followed by an M.S. in Operations Research and Control Theory from Guangxi University in 2008. He further advanced his expertise by completing a Ph.D. in Control Science and Engineering at Southeast University in 2016. Dr. Lan’s educational path demonstrates a consistent focus on control systems and computational methods, essential for modern automation and engineering solutions. Enhancing his academic profile, he has gained valuable international research experience, serving as a visiting scholar at the University of Texas at San Antonio (2014–2015) and Loughborough University in the UK (2024–2025). These global collaborations have significantly enriched his perspective, enabling him to engage with diverse research environments and apply advanced methodologies to his ongoing scientific pursuits.

🏆 Achievements & Recognition

Assoc. Prof. Dr. Qixun Lan has earned notable recognition for his contributions to control engineering and automation, most prominently through the receipt of four Henan Provincial Outstanding Scientific and Technological Achievement Awards. These honors underscore the regional and academic impact of his innovative research, reflecting both scholarly excellence and practical application. Beyond accolades, Dr. Lan has demonstrated strong leadership in scientific research by successfully presiding over a key project funded by the National Natural Science Foundation of China, one of the country’s most prestigious funding agencies. Complementing this national-level achievement, he has also spearheaded multiple research projects at the provincial and municipal levels, further contributing to technological advancement and academic development. His ability to attract competitive funding and deliver impactful outcomes highlights his influence and effectiveness as a leading researcher in his field. These accomplishments position him as a respected figure in China’s scientific community and beyond.

Research Focus

Assoc. Prof. Dr. Qixun Lan’s research primarily focuses on control theory, with specific expertise in finite-time control, sliding mode control, observer design, and nonlinear and stochastic systems. His work targets complex dynamical systems, including spacecraft, asteroid landing modules, permanent-magnet motors, and large-scale uncertain systems. Dr. Lan has made significant contributions to nonsmooth and output-feedback control, multi-disturbance rejection, and robust stabilization techniques, especially under conditions of uncertainty, time-delay, and structural complexity. His studies often incorporate advanced mathematical modeling, sampled-data systems, and adaptive mechanisms aimed at high-precision motion control and aerospace applications. With over 40 publications and strong citation metrics in journals like International Journal of Control, IET Control Theory & Applications, and Journal of Dynamic Systems, Measurement, and Control, Dr. Lan’s work plays a critical role in bridging theory with engineering practice. His interdisciplinary approach contributes significantly to modern automation, aerospace control systems, and nonlinear dynamics.

Publication Top Notes

📘 Global finite-time stabilisation for a class of stochastic nonlinear systems by output feedback – 78 citations, 2015 
📘 Continuous terminal sliding mode control with extended state observer for PMSM speed regulation system – 70 citations, 2017 
📘 Finite-time soft landing on asteroids using nonsingular terminal sliding mode control – 53 citations, 2014 
📘 Global output‐feedback stabilization for a class of stochastic nonlinear systems via sampled‐data control – 49 citations, 2017 
📘 Finite-time control for soft landing on an asteroid based on line-of-sight angle – 37 citations, 2014 
📘 Finite-time disturbance observer design and attitude tracking control of a rigid spacecraft – 29 citations, 2017 
📘 Finite‐time tracking control for nonlinear systems with multiple mismatched disturbances – 28 citations, 2020 
📘 Finite-time control for 6DOF spacecraft formation flying systems – 24 citations, 2015 
📘 Global decentralised stabilisation for uncertain large-scale feedforward nonlinear systems – 20 citations, 2014 
📘 Robust reliable guaranteed cost control for uncertain singular systems with time-delay – 17 citations, 2010 
📘 Finite‐Time Integral Sliding Mode Control for PM Linear Motors – 13 citations, 2013 
📘 Universal finite‐time observer design for hydraulic turbine systems – 12 citations, 2016 
📘 Finite-time stabilization of port-controlled Hamiltonian systems with disturbances – 11 citations, 2018 
📘 Global stabilization of cascaded systems with upper‐triangular structures – 9 citations, 2018

Xiao-Jie Peng | Control science | Best Researcher Award

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Assist. Prof. Dr. Xiao-Jie Peng | Control science | Best Researcher Award

Assist. Prof. Dr. Xiao-Jie Peng, Southwest University, China

Assist. Prof. Dr. Xiao-Jie Peng is an accomplished scholar in control theory and intelligent systems, currently serving as Assistant Professor at the College of Electronic and Information Engineering, Southwest University. He earned his Ph.D. in Automation from the China University of Geosciences (Wuhan) under Prof. Yong He, and a Bachelor’s degree in Electrical Engineering from Hunan University of Science and Technology. Dr. Peng’s research focuses on multi-agent systems, formation control, neural networks, and fractional-order systems, with significant contributions published in top-tier journals such as IEEE Transactions on Cybernetics and IEEE Transactions on Automation Science and Engineering. As a principal member of a National Natural Science Foundation of China project, he worked on advanced controller designs using Lyapunov functions. He has presented at international conferences like ICCAS and CCC and has received multiple honors, including the 2023 National Doctoral Graduate Scholarship. Dr. Peng is recognized for his innovative work in robust and intelligent control systems.

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Academic Background

Assist. Prof. Dr. Xiao-Jie Peng has built a strong academic foundation in the fields of automation and electronic engineering. He is currently serving as an Assistant Professor at the College of Electronic and Information Engineering, Southwest University, under the guidance of group leader Prof. Hongyi Li since June 2024. Dr. Peng earned his Doctoral degree from the School of Automation at China University of Geosciences (Wuhan), where he studied from September 2018 to June 2024 under the supervision of Prof. Yong He. His doctoral research focused on advanced control methods in complex systems, particularly multi-agent dynamics and delayed systems. Prior to his doctoral studies, he completed his Bachelor’s degree in Information and Electrical Engineering at Hunan University of Science and Technology from September 2013 to June 2017. This progressive academic journey has equipped him with deep expertise in system control, signal processing, and intelligent automation, laying the groundwork for his impactful research career.

Research Project Involvement

Assist. Prof. Dr. Xiao-Jie Peng served as a principal member of a significant research project funded by the National Natural Science Foundation of China (NSFC), titled “Analysis and Controller Design of Fractional-Order Systems Based on Relaxed-Type Lyapunov Functions” (Project No. 61973284). This project focused on developing innovative methods for analyzing and designing controllers for fractional-order dynamic systems, which are known for their ability to model real-world processes more accurately than traditional integer-order systems. Dr. Peng’s role involved theoretical development and practical implementation of relaxed-type Lyapunov functions to enhance the stability, robustness, and performance of control systems with fractional-order characteristics. His contributions were instrumental in advancing control theory and provided valuable tools for optimizing complex nonlinear and time-delayed systems. This research reflects Dr. Peng’s expertise in mathematical modeling, system dynamics, and advanced control engineering, establishing him as a forward-thinking researcher in his domain.

Certifications and Honors

Assist. Prof. Dr. Xiao-Jie Peng has achieved several certifications and prestigious honors that reflect his academic excellence and dedication. He holds the College English Test Band 6 certificate and Computer Level 2 certification, demonstrating his strong communication and technical proficiency. Throughout his academic journey, he has been recognized with multiple accolades. In 2023, he was awarded the esteemed Doctoral Graduate National Scholarship in December and secured the First Prize in Graduate Student Academic Achievement in November. Additionally, he received the Second Prize at the Technology Paper Presentation Conference in December 2023. In 2022, he earned the Scholarship for Class 84 of the School and was honored with the Party Branch Organization Committee Member’s Certificate. Earlier, in 2019, he received the Excellent Paper Award, further acknowledging his research quality. These distinctions highlight his outstanding performance in both academic and extracurricular engagements within the scientific and engineering communities.

Research Focus

Assist. Prof. Dr. Xiao-Jie Peng’s research is deeply rooted in the field of control theory and intelligent systems, with a particular emphasis on multi-agent systems, time-delay systems, and formation control. His work explores critical challenges in consensus control, robust stability, and optimization for complex dynamic systems, often involving nonlinearities, delays, and uncertainties. A prominent theme in his research is the development of advanced control strategies such as aperiodic sampled-data control, event-triggered fault-tolerant control, and order-reduction methods for improving system performance and resilience. Dr. Peng also integrates modern computational techniques like game-theoretical Q-learning into the domain of cyber-physical systems and distributed cooperative learning. His research contributions serve vital applications in areas such as robotics, neural networks, networked systems, and autonomous agents, making his work highly relevant to both theoretical advancements and real-world engineering problems in automation and intelligent control domains.

Publication Top Notes

📘 Consensus control and optimization of time-delayed multiagent systems: Analysis on different order-reduction methods – Cited by 39, 2024 📊🧠
📗 Time-Varying Formation Tracking Control and Optimization for Delayed Multi-Agent Systems With Exogenous Disturbances – Cited by 37, 2024 🤖🔁
📙 Consensus of multiagent systems with time-varying delays and switching topologies based on delay-product-type functionals – Cited by 26, 2022 ⌛🔗
📕 Time-varying formation tracking control of multi-leader multiagent systems with sampled-data – Cited by 20, 2023 📡👥
📘 Consensus of multi-agent systems with state and input delays via non-fragile protocol – Cited by 14, 2022 🧩⏱️
📗 Global exponential stability analysis of neural networks with a time-varying delay via some state-dependent zero equations – Cited by 13, 2020 🧠📈
📙 Bipartite consensus tracking control for periodically-varying-delayed multi-agent systems with uncertain switching topologies – Cited by 9, 2023 🔁🔒
📕 Aperiodic sampled‐data consensus control for homogeneous and heterogeneous multi‐agent systems: A looped‐functional method – Cited by 7, 2023 ⏲️⚙️
📘 Robust Time-Varying Formation Control of One-Sided Lipschitz Nonlinear Multiagent System With Delays via Optimization Algorithm – Cited by 3, 2025 📉🤖
📗 Optimal Tracking Control for Cyber-Physical Systems Under Mixed Attacks via Game-Theoretical Q-Learning – Cited by 2, 2025 🔐🎮
📙 Event-triggered adaptive fault-tolerant control for nonlinear multiagent systems with intermittent actuator faults – 2025 🛠️⚡
📕 Containment Control for Multi-Agent Systems under Directed Interaction Topologies with Time-Varying Delays – 2022 🔄🧭

Xinfeng Shao | Control Theory | Best Researcher Award

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Mr. Xinfeng Shao | Control Theory | Best Researcher Award

Lecturer at Liaoning University of Technology, China

Ph.D. in Control Science and Engineering from Northeastern University (2023), Dr. Xinfeng Shao is a Lecturer & Master’s Supervisor at Liaoning University of Technology (LUT). His research focuses on adaptive intelligent control, cyber-physical system security, event-triggered control, and fault-tolerant control. He has led multiple national-level projects, including the National Youth Science Foundation Project, and contributed to 10+ papers in top journals, with two highly cited in IEEE Transactions on Fuzzy Systems. 📝 His technical skills include MATLAB/Simulink and Python, and he is an active member of the Chinese Association of Automation and IEEE. 🌐

Publication Profile

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🎓 Educational Background

Dr. Xinfeng Shao earned his Ph.D. in Control Science and Engineering from Northeastern University in 2023. His research is focused on adaptive intelligent control, cyber-physical system security, event-triggered control, and fault-tolerant control. These areas are critical for enhancing the reliability and security of modern automation systems, especially in the context of cyber-physical systems (CPS). His innovative work aims to develop intelligent control frameworks that ensure optimal performance even under uncertain and adversarial conditions. Dr. Shao’s expertise contributes significantly to the advancement of automation and security technologies.

🔬 Research Projects

Dr. Xinfeng Shao has been a Principal Investigator for several key research initiatives, including the National Youth Science Foundation Project (Category C), the Liaoning Provincial Education Department Youth Cultivation Project, and the LUT Doctoral Research Startup Fund. These projects reflect his leadership in advancing research in control systems and cybersecurity. Additionally, Dr. Shao is a Key Participant in two National Natural Science Foundation of China (NSFC) Projects and the prestigious Liaoning “Xing Liao Talent Program” Leading Talent Project. His involvement in these projects highlights his significant contribution to the scientific community.

📚 Research Achievements

Dr. Xinfeng Shao has authored over 10 papers in prestigious journals like IEEE Transactions, with 2 papers being ESI Top 1% Highly Cited. His research has introduced novel control frameworks for ensuring the security of multi-agent systems (MASs) and improving nonlinear fault tolerance. These groundbreaking contributions are recognized internationally for advancing the fields of adaptive control and cybersecurity. His work continues to shape the future of control systems and automation, making a significant impact in both theoretical and applied research.

🧠 Research Focus

Dr. Xinfeng Shao’s research is centered around adaptive intelligent control, cyber-physical system (CPS) security, fault-tolerant control, and event-triggered control. His work explores the resilience and security of multi-agent systems (MASs), focusing on attack-resistant control frameworks in the presence of malicious disturbances like FDI attacks and DoS attacks. Dr. Shao also investigates nonlinear systems and distributed control strategies, developing secure formation control and adaptive fuzzy control techniques. His contributions are instrumental in enhancing the robustness and security of automated systems, improving fault tolerance and performance under uncertain conditions

Conclusion

Mr. Xinfeng Shao is highly suitable for the Research for Best Researcher Award. His innovative research in intelligent and secure control systems, impressive publication record, project leadership, and recognized academic contributions present a strong case for this honor. He exemplifies the qualities of a top-tier researcher advancing critical technologies in automation and cyber-physical security.

📚 Publications Top Notes

  • “Dynamic‐Event‐Based Predefined‐Time Secure Formation Control for Nonlinear Multiagent Systems Against FDI Attacks” – International Journal of Robust and Nonlinear Control, 2025. DOI: 10.1002/rnc.8017 🔒

  • “Adaptive Fault-Tolerant Consensus Tracking Control of Stochastic High-Order MASs Under FDI Attacks” – IEEE Transactions on Fuzzy Systems, 2024. DOI: 10.1109/TFUZZ.2024.3352076 🔄

  • “Event-based distributed resilient control strategy for microgrids subject to disturbances and hybrid attacks” – Applied Mathematics and Computation, 2023. DOI: 10.1016/j.amc.2023.128273 🌍

  • “Robust adaptive dynamic memory‐event‐triggered attitude control for nonlinear multi‐UAVs resist actuator hysteresis” – International Journal of Robust and Nonlinear Control, 2023. DOI: 10.1002/rnc.6821 🚁

  • “Event-based adaptive fuzzy fixed-time control for nonlinear interconnected systems with non-affine nonlinear faults” – Fuzzy Sets and Systems, 2022. DOI: 10.1016/j.fss.2021.08.005 ⚙️

  • “Neural-network-based adaptive secure control for nonstrict-feedback nonlinear interconnected systems under DoS attacks” – Neurocomputing, 2021. DOI: 10.1016/j.neucom.2021.03.087 🧠

  • “Fuzzy Adaptive Event-Triggered Secure Control for Stochastic Nonlinear High-Order MASs Subject to DoS Attacks and Actuator Faults” – IEEE Transactions on Fuzzy Systems, 2020. DOI: 10.1109/tfuzz.2020.3028657 🛡️

  • “Adaptive Fuzzy Prescribed Performance Control of Non-Triangular Structure Nonlinear Systems” – IEEE Transactions on Fuzzy Systems, 2019. DOI: 10.1109/tfuzz.2019.2937046 🔧

  • “Adaptive Fuzzy Prescribed Performance Control for MIMO Stochastic Nonlinear Systems” – IEEE Access, 2018. DOI: 10.1109/ACCESS.2018.2882634 🔄

  • “Adaptive prescribed performance decentralized control for stochastic nonlinear large-scale systems” – International Journal of Adaptive Control and Signal Processing, 2018. 📊

Weimin Xu | Adaptive Control | Best Researcher Award

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Mr. Weimin Xu | Adaptive Control | Best Researcher Award

Associate Professor at Shanghai Maritime University, China

Dr. Weimin Xu is an associate professor at Shanghai Maritime University, China. He earned his Bachelor’s degree in Automation from Northeastern University, China, in 1989, followed by his Master’s and PhD in Control Science in 1992 and 1997, respectively. In 2013, he participated in a one-year research program at the University of Southern California, USA. Dr. Xu has published over 30 academic papers and holds more than 20 patents, making significant contributions to control systems and automation. His expertise includes nonlinear systems, adaptive control, and intelligent control.

Publication Profile

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Educational Background

Dr. Weimin Xu obtained his Bachelor’s degree in Automation from Northeastern University, China, in 1989. He further pursued his Master’s and PhD degrees in Control Science at the same institution, completing them in 1992 and 1997, respectively. His strong academic foundation laid the groundwork for his successful research career. In 2013, he also participated in a one-year visiting research program at the University of Southern California’s School of Engineering, enhancing his international experience.

Professional Background

Since 2009, Dr. Xu has served as an associate professor at Shanghai Maritime University, China, where he combines teaching with scientific research. He has vast experience in mentoring students, advancing research in automation and control, and making significant contributions to both academic knowledge and industry applications. Additionally, his research at the University of Southern California during his 2013 visiting program enriched his global perspective and furthered his expertise in control science.

Awards and Honors

Dr. Xu has been recognized for his outstanding academic contributions, having obtained more than 20 invention patents, reflecting his innovative research in automation and control systems. His papers have been widely cited, underscoring the impact of his work in the field. While specific awards aren’t detailed, his continuous contributions to the academic community through publications and patents make him a distinguished figure in his field.

Research Focus

Dr. Xu’s research spans several areas of control theory, including nonlinear system theory, adaptive control theory, sliding control, intelligent control, and bridge crane control. His work primarily focuses on improving control systems and automating complex processes, contributing significantly to industries relying on advanced engineering solutions. He has published over 30 papers and holds numerous patents, demonstrating the practical application and innovation within his research areas.

Publication Top Notes

Robust adaptive decoupled-like sliding mode controller design based on iterative learning for overhead cranes
Year: 2025 | 📅

Ultra-local model based prescribed performance adaptive control of overhead cranes under uncertainties
Year: 2024 | 📅

Finite-time model-free robust synchronous control of multi-lift overhead cranes based on iterative learning
Year: 2024 | 📅

Conclusion

Dr. Weimin Xu is a highly qualified candidate for the “Best Researcher Award” due to his extensive academic background and significant contributions to the fields of automation and control science. With a Bachelor’s, Master’s, and PhD in relevant disciplines, his research spans nonlinear systems, adaptive control, sliding control, and intelligent control, all of which have real-world industrial applications. He has published over 30 academic papers and holds more than 20 patents, demonstrating both academic excellence and practical innovation. Since 2009, as an associate professor at Shanghai Maritime University, Dr. Xu has also contributed to mentoring the next generation of engineers and researchers, further solidifying his eligibility for this prestigious award.