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The Development Of Sliding Mode Observers For Robust Fault Estimation In Descriptor System


Prof. Tan Chee Pin (Edwin)

School of Engineering
Monash University Malaysia

Date & Time

Wednesday, 22 August 2018

6:30 am


Room 7-37, Haking Wong Building, HKU

The descriptor system representation (also known as singular systems, generalised systems, or differential algebraic systems) is a method to represent systems containing interrelated variables and subsystems with dynamics evolving on different time scales. It is more general than the standard state-space system, and exist across many different domains, with examples are found in various systems (engineering and otherwise).  When a system deviates from its expected behaviour, a fault is deemed to have occurred. These faults could eventually lead to system failure and costly downtime. Therefore estimating faults as they occur is vital so that precise and timely action can be taken to mitigate the fault and improve the reliability of the system. The estimation of faults in descriptor systems has not been widely explored, and this presentation will describe some of the work at Monash University Malaysia on the development of fault estimation schemes for descriptor systems.

Tan Chee Pin (Edwin) obtained the B.Eng. (Electrical & Electronic) from Leicester University, U.K. in 1998, and a Ph.D. from the same university in 
2002. Currently, he is an Associate Professor and also the Head of Mechatronics Engineering program at the School of Engineering, Monash University Malaysia. His research interests lie in the use of observers (mainly sliding mode observers) for robust state and fault estimation, and their applications in various systems such as soft robots, energy systems and smart city applications. He has published 40 papers in ISI journals, and 
serves as an Associate Editor of the IET Collaborative Intelligent Manufacturing, and also on the IEEE Control Systems Society Conference Editorial Board.

Research Areas:

Robotics and Control

Contact for


Prof. J. Lam

+(852) 3917 2805

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