Dr. Jun Yang, Autonomous and Electric Vehicles, Best Researcher Award
- Ā Doctorate at Loughborough University, United KingdomĀ
Dr. Jun Yang is a Reader in Electric and Autonomous Vehicles at Loughborough University, UK. With a Ph.D. in Control Theory & Control Engineering from Southeast University, China, Dr. Yang’s expertise lies in control engineering, advanced control theory, and autonomous system technologies. He has made significant contributions to disturbance rejection control and has a proven track record of leadership in academia and scientific organizations.
Author Metrics
Dr. Yang’s research impact is evident in his author metrics, with a high citation count and h-index reflecting the significance of his contributions. His work is widely cited in the field of control engineering and has been recognized through various awards and accolades. Additionally, his publications in reputable journals and conferences contribute to the advancement of knowledge in electric and autonomous vehicles.
- 14,066 citations received across 9,372 documents, indicating the impact and reach of his research.
- He has authored 385 documents, reflecting his extensive scholarly output.
- Dr. Yang has an h-index of 47, which is a measure of both the productivity and citation impact of his publications.
These metrics demonstrate Dr. Yang’s significant contributions to his field and the recognition his work has received within the academic community. The profile also offers options to connect with his Mendeley account or claim the author account, providing opportunities for collaboration and networking within the research community.
Education
Dr. Yang completed his Bachelor’s degree in Industrial Automation from Northeastern University, China, followed by a Ph.D. in Control Theory & Control Engineering from Southeast University. His doctoral research focused on disturbance rejection control for complex dynamic systems, laying the foundation for his subsequent work in control engineering and autonomous systems.
Research Focus
Dr. Yang’s research interests encompass control engineering, advanced control theory, and autonomous system technologies. He specializes in multiple disturbance modeling and estimation, disturbance rejection, motion planning, and integrated perceptual control for electric, mechatronic, and autonomous systems. His work also extends to areas such as model predictive control, nonlinear control, and safety-critical control.
Professional Journey
Dr. Yang’s academic career spans over a decade, during which he held various positions at Southeast University, China, including Lecturer, Associate Professor, and Full Professor. He has also undertaken visiting scholar roles at esteemed institutions such as Imperial College London and Nanyang Technological University. Currently, he serves as a Reader at Loughborough University, leading research and teaching initiatives in Electric and Autonomous Vehicles.
Honors & Awards
Dr. Yang has received numerous prestigious awards and honors for his contributions to the field of control engineering. These include being named a Fellow of IEEE and AAIA, winning the EPSRC New Investigator Award, and receiving the Gold Medal at the International Exhibition of Inventions of Geneva. He is also recognized as one of the World’s Top 2% Scientists by Stanford University and a Highly Cited Chinese Researcher by Elsevier.
Research Timeline
Throughout his research career, Dr. Yang has pursued a diverse range of projects and collaborations, leading to significant advancements in control engineering and autonomous systems. From his early work on disturbance rejection control to his recent projects on modulator-free performance-oriented control and visual servoing landing control of UAVs, Dr. Yang’s research timeline showcases a trajectory of continuous innovation and impact in his field.
Publications Top Noted & Contributions
Dr. Yang has authored a prolific body of work encompassing journal articles, conference papers, and book chapters. His research contributions span a wide range of topics, including disturbance observer-based control, model predictive control, and autonomous system technologies. His publications have garnered recognition, including Best Paper Awards from IEEE and IEEJ, and have been widely cited within the scientific community.
Continuous finiteātime sliding mode control for uncertain nonlinear systems with applications to DCāDC buck converters (2019, Asian Journal of Control):
- Authors: Z. Zhao, S. Li, J. Yang
- Focus: This paper discusses continuous finite-time sliding mode control, particularly applied to uncertain nonlinear systems, with a specific focus on DC-DC buck converters.
Realization of exact tracking control for nonlinear systems via a nonrecursive dynamic design (2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems):
- Authors: C. Zhang, J. Yang, C. Wen, L. Wang, S. Li
- Focus: The paper presents a method for achieving exact tracking control for nonlinear systems through a nonrecursive dynamic design approach.
Model predictive control for DC-DC buck power converter-DC motor system with uncertainties using a GPI observer (2017, 36th Chinese Control Conference):
- Authors: H. Wu, L. Zhang, J. Yang, S. Li
- Focus: This work discusses the implementation of model predictive control for a system consisting of a DC-DC buck power converter and a DC motor, with consideration of uncertainties, utilizing a GPI observer.
Sliding-Mode-Based Robust Output Regulation and Its Application in PMSM Servo Systems (2022, IEEE Transactions on Industrial Electronics):
- Authors: L. Zhang, Z. Chen, X. Yu, J. Yang, S. Li
- Focus: This paper presents sliding-mode-based robust output regulation techniques and their application in Permanent Magnet Synchronous Motor (PMSM) servo systems.
Finite-time path following control for small-scale fixed-wing UAVs under wind disturbances (Journal of the Franklin Institute, 2017):
- Authors: X. Yu, J. Yang, S. Li
- Focus: The paper discusses finite-time path following control strategies for small-scale fixed-wing UAVs (Unmanned Aerial Vehicles), particularly considering wind disturbances.