Dr. Gopaluni’s primary research interests are in Process Modeling and Control. He is interested in developing and studying the properties of data-based models for a variety of chemical and biological systems. These systems are typically nonlinear, hybrid and time varying, and their measurements are often noisy and irregular. The thrust of his research is on developing high quality models for such processes and adapting them to reflect process changes. His research interests also span a wide range of other areas including identification for control, model predictive controllers, adaptive control, and performance monitoring and assessment.
The current focus of his group includes, but is not limited to, the following:
- Identification and Experiment Design for hybrid and irregularly sampled processes
- Adaptive Estimation of irregularly sampled processes
- Adaptation of above methods for small data sets and nonlinear systems
- Applications of these approaches in the Oil & Gas and Pulp & paper industry, and Biomedical engineering
Please see his personal page for further details on specific projects.
For publications, visit his website.