Control, Monitoring & Optimization
- Optimal and model predictive control (MPC) of chemical packed-bed and tubular reactors
Classical and modern control controller realizations are merged and implemented in process systems of industrial interest.
In particular, practical optimal control formulations have been developed in order to address important aspects of actuation constraints, state/output constraints, and optimality of the control law.
- Optimal and model predictive control of crystal growth processes
The optimal control of crystal growth processes is one of the open problems in the semiconductor process industry. In particular, the CZ-Si crystal growth is a prime example of a multi-physics system in which the pulling of the crystal and thermal effects affect the quality of the grown crystal. The fluctuations in the crystal temperature distribution and the rate at which the crystal cools may induce significant thermoelastic stresses, leading to defect and dislocation generation.
In addition, the current crystal growth processes operate at a slow crystal growth rate (usually 3-5cm/h). Therefore, it is essential to provide an optimal, faster growth rate that will be integrated with the temperature regulation and pulling mechanism control.
- Mixing in chemical reaction systems
Understanding the viscous mixing is technologically crucial in the context of materials processing, reactive and non-reactive polymer processing, food processing and/or stabilization of hazardous waste. Mixing barriers are a consequence of particular time-varying flow features which can be identified by the framework of Lagrangian coherent structures.
Associate Professor at the University of Alberta Chemical and Materials Engineering Department.
B.Sc. degree (1997) from the Belgrade University (Serbia); M.S. degree (2001) from the Texas A&M University (Texas) and Ph.D. in 2005 from the Henry Samueli School of Engineering and Applied Science at University of California in Los Angeles (UCLA)
Independent post-doctoral researcher position at the Cardiology Division of the UCLA's David Geen School of Medicine from 2006 to 2009. Recipient of the American Heart Association (AHA) Western States Aliate Post-doctoral Grant Award (2007-2009) and of the O. Hugo Schuck Award for Applications, from the American Automatic Control Council (AACC) in 2007.
Research interests include systems engineering, with the emphasis on model predictive control of distributed parameter systems, dynamics and optimization of material and chemical process operations, computational modelling and simulation of biological systems (cardiac electrophysiological systems) and biomedical engineering.
Reviewer for the IEEE Transaction on Automatic Control, IEEE Transaction on Control Systems Technology, Automatica, Industrial & Engineering Chemical Research, International Journal of System Science, American Control Conference, Conference on Decision and Control, and program coordinator for the AIChE Annual Meetings (2014).