Zhan Shu

Area of Study / Keywords

Control Systems Reinforcement Learning Power Electronics Building Systems Theoretical Biology

About

Zhan Shu received his B.Eng. degree in Automation from Huazhong University of Science and Technology in 2003, and the Ph.D. degree in Control Engineering from The University of Hong Kong in 2008 under the supervision of Prof. James Lam. For his doctoral research, he received the award for Outstanding Research Postgraduate Student of the University of Hong Kong.

He was a Post-Doctoral Fellow in the Hamilton Institute, National University of Ireland, Maynooth, from 2009 to 2011, working with Prof. Richard H. Middleton, and a Lecturer in the Faculty of Engineering and Physical Sciences, the University of Southampton from 2011 to 2019. Since 2020, he has been a faculty member at the Department of Electrical and Computer Engineering, University of Alberta, where he is currently a Professor.

He is a Senior Member of IEEE, Member of IET, and an invited reviewer of Mathematical Review of the American Mathematical Society. In addition, he serves as an Associate Editor for Mathematical Problems in Engineering, Asian Journal of Control, Journal of The Franklin Institute, Proc. IMechE, Part I: Journal of Systems and Control Engineering, IET Electronics Letters, IET Control Theory and Applications, IEEE Transactions on Automatic Control, and a member of the IEEE Control Systems Society Conference Editorial Board. 

Research

Research Interests

My primary research area is control systems, involving both theory and application. In particular, I am interested in connected/networked systems and related cyber-physical fusion. At the heart of my research are developing theories, tools, and methods to address the challenges arising from the connection of physical entities and unlocking the power of cyber-physical fusion. My current research interests include, but are not limited to,

Theory:

• Networked control 
• Learning-based control
• Distributed systems and control
• Hybrid systems
• Autonomous systems
• Stochastic dynamic systems

Applications:

• Control of power electronic converters (multilevel converters particularly)
• Autonomous operation and control of mobile robots (UAVs and UGVs)
• Energy efficient operation and control of building systems 
• A control-theoretic perspective on biological systems (immune system and endocrine system)

ECE 360 - Control Systems I

Linear system models. Time response and stability. Block diagrams and signal flow graphs. Feedback control system characteristics. Dynamic compensation. Root locus analysis and design. Frequency response analysis and design. Prerequisites: ECE 203 or E E 250, and ECE 240 or E E 238. Credit may be obtained in only one of ECE 360, ECE 362, E E 357, E E 462 or E E 469.

ECE 561 - Nonlinear Control Systems

Nonlinear system examples. Stability in the sense of Lyapunov. Lyapunov functions. The invariance principle. Lyapunov-based design. Backstepping. Input-output stability. Passivity and small-gain theorems. Input to state stability. Dissipativity. Note: Only one of the following courses may be taken for credit: ECE 561 or E E 666.

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