Hector Budman is a Professor in the Department of Chemical Engineering at the University of Waterloo.
Professor Budman’s research is multi-disciplinary, leading him to undertake collaborative work in pharmaceuticals, water treatment, minerals processing, and pulp and paper industries.
Typically when a system is modeled, there is some difference between the actual process and the model. As a result, control systems based on process models have to be designed to compensate for the difference. Professor Budman’s research investigates the application of robust control theory to advance control techniques such as Model Predictive Control, Inferential Control and Non-Linear Control. In order to deal with the model inaccuracy, Professor Budman studies methods for quantifying the model uncertainty from experimental data. He also designs steady state estimators so that controlled variables can be inferred from secondary measurements; such as controlling concentrations using temperatures.
Furthermore, chemical processes are generally non-linear, especially when operated in a wide range of operating conditions. Hence, these processes need to be controlled using non-linear controllers. The obstacle that Professor Budman’s work seeks to overcome when designing non-linear controllers is to obtain a simple model of the processes under study. Typical processes studied are bioreactions, solidification of metal, cells and tissues.
In addition to his research work, Professor Budman has authored and co-authored over 150 journal publications in process modelling and controls with applications to biotechnology and reaction systems. He also co-authored the book “Periodic Operations of Chemical Reactors” and chaired the October 2014 Canadian Conference in Chemical Engineering.
- Process Control
- Modelling Of Chemical Systems
- Monitoring Of Chemical Processes
- Inferential Sensors
- Process Systems Engineering
- Robust Control
- Modelling And Control Of Nonlinear Processes
- Chemical Process Control
- Model Predictive Control
- Systems Biology
- Control And Optimization Of Biological Processes
- Metabolic Flux Analysis
- Dynamic Metabolic Flux Models
- Run-to-run (batch To Batch) Optimization Of Pharmaceutical Process
- Monitoring/Fault Detection Of Chemical And Biological/biotechnological Processes
- Multivariate Statistical Methods For Monitoring And Fault Detection
- Inferential (soft) Sensors
- 1987, Doctorate, Mechanical Engineering, Technion - Israel Institute of Technology
- 1983, Master's, Mechanical Engineering, Technion - Israel Institute of Technology
- 1979, Bachelor's, Mechanical Engineering, Technion - Israel Institute of Technology
- CHE 522 - Advanced Process Dynamics and Control
- CHE 624 - Advanced Process Dynamics and Control
- CHE 524 - Process Control Laboratory
- CHE 420 - Introduction to Process Control
- Nikdel, Ali and Braatz, Richard D and Budman, Hector M, A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis, Bioprocess and biosystems engineering, 2018, 1 - 15
- Tangpromphan, Preuk and Budman, Hector and Jaree, Attasak, A simplified strategy to reduce the desorbent consumption and equipment installed in a three-zone simulated moving bed process for the separation of glucose and fructose, Chemical Engineering and Processing-Process Intensification, 2018
- Aghamohseni, Hengameh and Spearman, Maureen and Ohadi, Kaveh and Braasch, Katrin and Moo-Young, Murray and Butler, Michael and Budman, Hector M, A semi-empirical glycosylation model of a camelid monoclonal antibody under hypothermia cell culture conditions, Journal of industrial microbiology & biotechnology, 44(7), 2017, 1005 - 1020
- Nikdel, Ali and Budman, Hector, Identification of active constraints in dynamic flux balance analysis, Biotechnology progress, 33(1), 2017, 26 - 36
- Du, Yuncheng and Budman, Hector M and Duever, Thomas A, Segmentation and Quantitative Analysis of Apoptosis of Chinese Hamster Ovary Cells from Fluorescence Microscopy Images, Microscopy and Microanalysis, 23(3), 2017, 569 - 583