Ravi Gudi's Research Group

Achieving operational excellence (OE) in any process system involves real-time prediction, optimization, monitoring, and control for proactive decisions. Digital Twins (DT) and enabling technologies from the Industrial Internet of Things (IIoT) and machine learning offer great potential to achieve these desired OE goals. Work in my research group has focused on aspects related to development of…

Advances in Machine Learning (ML) algorithms and automatic differentiation (AD) have facilitated knowledge representation of various cause–effect relationships, that are conventionally represented by PDEs (higher order), to be captured in nonlinear mapping frameworks such as Neural Networks (NN).  Using such knowledge representation frameworks, physics laws/mechanistic models are…

Chemical Looping reactor configurations, especially in the context of coal combustion offer merits in terms of oxygen supply without direct contact of fuel with air. Metal oxides that serve as oxygen carriers are looped between two reactors, during which they separately deliver oxygen to the fuel and then pick up oxygen from the air stream. This leads to fuel combustion and the…

One of the key facets of water management in industries is the focus on the 3Rs, viz. Recycle, Reuse and Regeneration. Research efforts in my group have looked at facile ways of intra as well as inter plant opportunities for implementing the 3Rs to minimize water footprint in industrial practices. Approaches based on using super-structure based optimization methods have been…

1. Pankhedkar, N., Sartape, R., Gudi, R.D., Singh, M., Biswas, P., “System-level feasibility analysis of a novel chemical looping combustion integrated with electrochemical CO2 reduction”, Accepted for publication in Sustainable Energy and Fuels Journal, (2024).
2. S Mehla, RD Gudi, DD Mandaliya, T Hisatomi, K Domen, SK Bhargava, “Additive Fertigung als die Zukunft der grünen chemischen Ingenieurwissenschaften, “Additive Fertigung für Chemiewissenschaften und Chemieingenieurwesen, 269-344, 2024
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1. Patel, R., Bhartiya,S. and Gudi, R.D., “ Model Predictive Control using Physics Informed Neural Networks for Process Systems.” Accepted for Presentation in IFAC-ADCHEM, Toronto (July 2024).

2. Keshwani, R., Mukhopadhyay, S., Gudi, R., Joshi, G., “A Novel Tuning Scheme for Fast Norm Optimal Iterative Learning Controller”, In International Conference on Advances in Control, Optimization of Dynamic Systems, (2024).
3. Keshwani, R., Mukhopadhyay,…