Implementation and performance assessment of a real-time optimization system on a virtual fluidized-bed catalytic-cracking plant (2020)
This thesis develops and evaluates RTO implementation in a FCCU virtual plant, taking into account each RTO stage (noise elimination, steady-state detection, data validation, parameter estimation, and optimization). The dynamic data to carry out this analysis were obtained from an FCCU virtual plant based on a dynamic deterministic model developed in Matlab®. The model output data were contaminated with Gaussian and gross errors to simulate measurements from a real plant. For denoising, steady-state detection, data reconciliation, parameter estimation, and optimization, different strategies and algorithms were studied and assessed, while a decentralized PID was proposed for the control system. Finally, the most appropriate strategies for the case study were implemented and their performance was fully evaluated.