Afzali, Sayyed Faridoddin
Khan, Kamil A.
MacGregor, John F.
Madabhushi, Pranav Bhaswanth
Marlin, Thomas E.
Swartz, Chris L. E.
Supervised by Dr. Chris Swartz
B.Eng., Chemical Engineering, Universiti Teknologi Malaysia, Malaysia
M.Eng., Chemical Engineering, Universiti Teknologi Malaysia, Malaysia
Integration of Dynamic Real-Time Optimization (D-RTO) and Model Predictive Control (MPC)
The current global economic environment requires more agile plant operation in order to optimize cost, profit and productivity under flexible operating conditions with respect to market demands. This requires judicious decisions by the economic optimizing control strategy, which is distributed within the so-called plant decision hierarchy. Such strategy drives process plants to be responsive to any changes in operational well as economic variables in order to seek and remain at the highest profit margin.
This project aims to improve plant economics during transient operations using dynamic optimization. There are two main objectives in this project. The first objective is to systematically integrate dynamic real-time optimization (D-RTO) and model predictive control (MPC) for calculation and implementation of economically optimal set point trajectories of manipulated and controlled variables for process plants under transient operations. The second one is to design and implement the two-layer framework of integrated D-RTO and MPC for processes under extreme operations that includes plant startup, shutdown and partial shutdown.
- Jamaludin, M. Z., Swartz, C. L. E. Dynamic real-time optimization with closed-loop prediction, AIChE J, (2017) [ Publisher Version ]
- Jamaludin, M. Z., Swartz, C. L. E. Approximation of closed-loop prediction for dynamic real-time optimization calculations, Computers & Chemical Engineering,, 103 23-38 (2017) [ Publisher Version ]