Control Group Members
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Dr Michael Z.Q. Chen
Previous Member
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| Background |
Michael Chen graduated from Nanyang Technological University with a B.Eng. degree in Electrical and Electronic Engineering, and from Cambridge University with a Ph.D. degree in Control Engineering under the supervision of Professor Malcolm Smith.
Dr. Chen is a Fellow of the Cambridge Philosophical Society, a Life Fellow of the Cambridge Overseas Trust, and a member of the IEEE. His research interests include: passive network synthesis, vehicle suspensions, complex networks, and statistical mechanics.
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| Research Overview |
One strand of his work has explored the passive network synthesis in mechanical systems and electrical systems. In the past, mechanical network design has been based primarily on an analysis approach in which an arrangement of mechanical elements was tested, the results noted and compared with a specific response, and the network then modified to correct for errors. In this sense, analysis represents a trial and error approach to mechanical network design which relies heavily on the designers experience. The increasing complexity of modern mechanical systems plus requirements of maintaining small volume, light weight, and high reliability have led to the need for a more systematic design process. In particular, he has been focussing on passive networks (networks containing passive elements only and on power sources), which are easier to construct and implement than active networks (networks containing power sources).
Another strand of his work has been exploring the complexity of networks, in particular, the flocking and swarming dynamics in natural bio-groups and the consensus problem. In the past decade, the study of complex networks has become a booming research field with a distinct interdisciplinary character. Scientists have been looking for some common, possibly universal features of the collective behaviours of animals, bacteria, cells, molecular motors, as well as driven granular objects. The collective motion of a group of autonomous agents is currently a subject of intensive research that has potential applications in biology, physics, and engineering. Solving the flocking and swarming problems using distributed computational methods has direct implications on sensor network data fusion, load balancing, unmanned air vehicles (UAVs), attitude alignment of satellite clusters, congestion control of communication networks, multi-agent formation control, and so on.
He is also interested in systems and control theory in general. |
| Teaching |
Project 12 Demo (Multivariable Process Control)
IB P6 Linear systems and control + Communications
3F2 Multivariable System Control
September 2006 - July 2007, Teaching Assistant for Div. F, CUED.
IA C++ Computing
IB Exp. 12, Spectrum Analysis
IB Exp. 22, Data Transmissions
IIA Flight Control (Marking)
Teaching@Leicester:
EG1070 Mathematics II (1st year)
EG2050 Dynamics of Engineering Systems (2nd year)
EG3160 Dynamics of Mechanical Systems (3rd year/MSc)
EG7015 Robust Control (MSc)
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