Process Control

Dual Adaptive and Predictive Control of Nonlinear and Distributed Systems

Model predictive control (MPC) is the most widely used multivariable control scheme in industrial control. Success of any MPC scheme critically depends on prediction models. The closed loop performance of an MPC scheme can deteriorate over a period of time if the prediction model is not updated to account for the changing operating conditions. The adaptive (self-learning) control schemes that solve both identification and control problems simultaneously provide an attractive option to alleviate this problem.

Online Optimizing Control of Nonlinear Processes using Machine Learning Techniques

Process industry is moving towards use of nonlinear dynamic models in advanced process control solutions such as fault tolerant control, process monitoring and online real time optimization. Development of control relevant models that capture system behavior over a wide range is always a challenge in chemical processes because of tight mass and energy integrations through recycle

Plantwide real time optimization, control and estimation of a solar thermal power plant

This work will deal with plantwide simulation studies for real time optimization, control and estimation using a dynamic model of a solar thermal power plant. The model was developed by an earlier PhD student and mimicks an actual 1 MW hybrid solar thermal power plant designed, commissioned and installed by a team from IIT Bombay. 

Distributed control architecture synthesis

Control of integrated networks is challenging due to strong interactions between variables (limiting performance of decentralized controllers) and large system size (difficult design of a centralized controller). In this context, distributed controllers pose an optimal architecture with reduced system size and inclusion of key interactions. A key question is how to decompose an integrated system into distributed architecture. We address this problem via structural analysis. Specifically, we abstract the control system into an equivalent graph.

Enabling Fast Charging and Safe Operation for Li-ion Battery: Modeling, Simulation and Optimization

Battery charging time is one of the most critical factors that will govern the penetration of electric vehicle in the market. Reduction in battery charging time is also desirable for portable electronics including cellphones. Significant research is underway to reduce the charging time of a lithium-ion battery. Ensuring safety while fast charging as well as discharging is also crucial for battery usage.

Design aspects of energy-integrated batch distillation

Distillation is one of the most commonly used as well as the most significant contributor of energy in chemical processing complex. Energy integration can improve the sustainability of the process by reducing utility requirement in batch distillation. However, operation of such columns is challenging. Traditionally, design of such systems is pursued without giving any consideration for operation. In the light of this, this project aims as developing a design framework for such distillation columns to address operational challenges.