Xiao-Jie Peng | Control science | Best Researcher Award

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.

Publication Profile

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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 methodsCited by 39, 2024 📊🧠
📗 Time-Varying Formation Tracking Control and Optimization for Delayed Multi-Agent Systems With Exogenous DisturbancesCited by 37, 2024 🤖🔁
📙 Consensus of multiagent systems with time-varying delays and switching topologies based on delay-product-type functionalsCited by 26, 2022 ⌛🔗
📕 Time-varying formation tracking control of multi-leader multiagent systems with sampled-dataCited by 20, 2023 📡👥
📘 Consensus of multi-agent systems with state and input delays via non-fragile protocolCited by 14, 2022 🧩⏱️
📗 Global exponential stability analysis of neural networks with a time-varying delay via some state-dependent zero equationsCited by 13, 2020 🧠📈
📙 Bipartite consensus tracking control for periodically-varying-delayed multi-agent systems with uncertain switching topologiesCited by 9, 2023 🔁🔒
📕 Aperiodic sampled‐data consensus control for homogeneous and heterogeneous multi‐agent systems: A looped‐functional methodCited by 7, 2023 ⏲️⚙️
📘 Robust Time-Varying Formation Control of One-Sided Lipschitz Nonlinear Multiagent System With Delays via Optimization AlgorithmCited by 3, 2025 📉🤖
📗 Optimal Tracking Control for Cyber-Physical Systems Under Mixed Attacks via Game-Theoretical Q-LearningCited by 2, 2025 🔐🎮
📙 Event-triggered adaptive fault-tolerant control for nonlinear multiagent systems with intermittent actuator faults2025 🛠️⚡
📕 Containment Control for Multi-Agent Systems under Directed Interaction Topologies with Time-Varying Delays 2022 🔄🧭

Xinfeng Shao | Control Theory | Best Researcher Award

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

Orcid

🎓 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. 📊