Enhancing the Efficiency and Reliability of UAV Systems: A Lyapunov-Based Stabilizing Model Predictive Control Framework
Join the IEEE Toronto Instrumentation & Measurement – Robotics & Automation Joint Chapter for a technical talk presented by Dr. Binyan Xu from University of Guelph.
Monday, July 7, 2025 @ 10:30 – 11:30 AM (EST)
Abstract: The use of Unmanned Aerial Vehicles (UAVs) has expanded significantly over recent decades, driven by their flexibility, efficiency, cost-effectiveness, and capability to operate in dangerous or inaccessible environments. With rising demands, UAV systems are increasingly expected to achieve higher levels of autonomy. Model predictive control (MPC), an advanced control methodology that leverages online optimization, provides notable advantages such as optimal performance, efficient handling of multivariable systems, and explicit constraint management, making it a promising solution for UAV control challenges. However, ensuring closed-loop performance with manageable computational demands remains challenging due to the highly nonlinear dynamics of UAVs and the computational complexity of MPC.
This talk introduces a Lyapunov-based MPC framework designed specifically to address these challenges, offering stabilized and computationally efficient MPC strategies tailored for UAV applications. Applications of this framework, including trajectory tracking and formation control, will be demonstrated to illustrate its effectiveness. Additionally, the integration of this framework with other Lyapunov-based control techniques for handling unexpected actuator faults and communication disruptions will be discussed, highlighting its potential to further enhance UAV operational efficiency and reliability.
Date and Time
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- Date: 07 Jul 2025
- Time: 02:30 PM UTC to 03:30 PM UTC
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- Starts 01 June 2025 04:00 AM UTC
- Ends 06 July 2025 04:00 AM UTC
- No Admission Charge
Speakers
Binyan Xu, Ph.D.
Biography:
Bio: Dr. Binyan Xu received her BEng. in Automation Engineering and MSc. in Control Theory and Control Engineering from Nanjing University of Aeronautics and Astronautics, Jiangsu, China, in 2016 and 2019, respectively. She completed her Ph.D. in Mechanical Engineering at the University of Victoria, Victoria, BC, Canada, in 2024. Following her doctoral studies, she joined the School of Engineering at the University of Guelph, Guelph, Ontario, Canada, as an Assistant Professor. Her current research interests encompass model predictive control, fault-tolerant control, and nonlinear control, particularly in applications related to mechatronic systems.