Tan Chee Pin is an Associate Professor, and Head of the Mechatronics Engineering degree program at Monash University Malaysia. His primary research interest lies in observers, where he has developed model-based observer configurations and design methods to accurately estimate the unknown signals of a system at the minimum possible cost (e.g. less sensors, less accurate data/model). The estimates of these unknown signals could then be used for condition monitoring and prediction of future phenomena, which could result in cost savings, increased productivity, energy savings and prevention of breakdowns, just to name a few benefits. He has published many papers in the top journals such as IEEE Transactions in Automatic Control, Automatica, International Journal of Robust and Nonlinear Control, and Journal of the Franklin Institute. He has also successfully applied those methods to other areas such as lighting, soft robotics, traffic and energy management. He has attracted RM1.5m in research funding from government agencies and industry, and has supervised 7 students to successful PhD completion, and is currently supervising another 13.

Dr. Tan teaches with a student-centric approach, and makes it easy for students to understand complicated subjects such as Control Theory. For these, he has won several awards internally within Monash University, and was also a finalist in the 2018 National Outstanding Educator’s Award.

My primary research interest lies in observers, where I have developed model-based observer configurations and design methods to accurately estimate the unknown signals of a system at the minimum possible cost (e.g. less sensors, less accurate data/model). The estimates of these unknown signals could then be used for condition monitoring and prediction of future phenomena, which could result in cost savings, increased productivity, energy savings and prevention of breakdowns, just to name a few benefits.

The results of the research can be applied to a wide variety of dynamic systems (machinery, biological systems, and even man-made non-physical systems such as traffic control). Examples of applications are given as follows (but not limited to)

• prediction of traffic congestion
• reduction of down-times and optimization in industrial processes
• optimization of battery life

• TRC2001 - Introduction to Systems Engineering
• ECE4032 - Advanced Control
• MEC4418 - Control Systems