WELCOME TO PRECEDE 2023

Tutorial Proposal

“Model Predictive Control under Disturbances: Performance, Safety, and Stability”

Instructors:  

Jun Yang, Department of Aeronautical and Automotive Engineering, Loughborough University, j.yang3@lboro.ac.uk

Chuanlin Zhang, College of Automation Engineering, Shanghai University of Electric Power, clzhang@shiep.edu.cn

Yunda Yan, School of Engineering and Sustainable Development, De Montfort University, yunda.yan@dmu.ac.uk

Abstract: 

For real-world control systems, different nonlinearities, variations of model parameters, unmodelled internal dynamics, noises, and external disturbances make control design a very challenging work. This tutorial will discuss the state-of-the-art design and analysis methods and tools for formal model predictive control under disturbances. Compared with other high gain control, optimal control methods, and disturbance observer-based control methods, disturbance rejection model predictive control (DR-MPC) solutions provide a different way to deliver optimization control in the presence of disturbances and constraints, thus can effectively improve the performance of closed-loop systems and guarantee safety under extreme conditions. New research developments and results will be introduced, including performance improvement, safety-critical specification, stability, and recursive feasibility under considerable disturbances. Considering the characteristics of the real-world mechatronic systems like machines and drives, power converters and unmanned arial vehicles, several new MPC control schemes are presented with experimental verification results.

Biographies:

Jun Yang is a Senior Lecturer in Electric and Autonomous Vehicles at Loughborough University. He has been engaged in nonlinear and intelligent disturbance rejection control theory, and autonomous system theory with applications to intelligent mechatronic and robotic systems. He was elevated as an IEEE Fellow in 2022 and an IET Fellow in 2020. He is the recipient of EPSRC New Investigator Award in 2022, the Winner of Gold Medal of International Exhibition of Inventions of Geneva in 2022, Premium Award for best paper of IET Control Theory and Applications in 2017, ICI Prize for best paper of Transactions of the Institute of Measurement and Control in 2016. He has published a monograph and more than 100 journal papers, which have gained over 11,000 citations on Google Scholars. He serves as Associate/Technical Editors of prestigious international journals like IEEE Transactions on Industrial Electronics, IEEE/ASME Transactions on Mechatronics, IEEE Open Journal of Industrial Electronics Society, etc.

Chuanlin Zhang is the executive dean of College of Computer Science and Technology, Shanghai University of Electric Power. He received the B.S. degree in mathematics and the Ph.D. degree in control theory and control engineering from the School of Automation, Southeast University, Nanjing, China, in 2008 and 2014, respectively. He was a Visiting Ph.D. Student with the Department of Electrical and Computer Engineering, University of Texas at San Antonio, USA, from 2011 to 2012; a Visiting Scholar with the Energy Research Institute, Nanyang Technological University, Singapore, from 2016 to 2017. a Visiting Scholar with the Advanced Robotic Center, National University of Singapore, from 2017 to 2018. His research interests include nonlinear system control theory and applications for distributed power systems and intelligent autonomous systems. He has authored more than 70 SCI indexed papers, in which over 30 papers publicated in IEEE Transaction series. He has hold a number of scientific research projects such as the National Natural Science Foundation of China, Shanghai Rising-Star Program, and Shanghai Natural Science Foundation. Currently, he is a Distinguished Professor of Oriental Scholars at Shanghai, Executive Director of the IEEE PES Smart Grid and New Technology (China) Intelligent IoT and Control Technology Subcommittee, Deputy Director of the Academic Committee of Shanghai Electronics and Electrical Appliances Association, Director of Shanghai Automation Society, and Senior Member of IEEE.

Yunda Yan is a Lecturer in Control Engineering at the School of Engineering and Sustainable Development, De Montfort University (DMU), UK. He received a PhD degree in Control Science and Engineering from Southeast University, China, in 2019, and a BEng degree in Automation from Southeast University in 2013. Prior to joining DMU, he worked as a post-doctoral researcher at the Centre of Autonomous Systems, Loughborough University, UK, from Jun. 2020 to Dec. 2022. At Loughborough University, he worked on several projects related to manufacturing, aerial robotics, and optimization-based control. His current research focuses on the safety-critical control design for autonomous systems, especially related to optimization and learning-based methods. He is particularly interested in developing fundamental methods and algorithms that embedding or enhancing the safety of autonomous systems in complex real-world environments with unknown or uncertain disturbances.