Health-aware control and model-based prognostics of a subsea oil and gas separation system - Bernardino, Lucas Ferreira (2019)
The exploitation of fields with high CO2 content is challenging, due to the low economic value and the environmental impact associated with this component. In this context, a significant use for the generated CO2 is its reinjection into the reservoir, and subsea CO2 separation allows for more efficient processing. Prognostics is a key activity in this process, due to the necessity of minimizing intervention in equipment. The main objective of this work is to investigate the health-aware control of a subsea CO2 separation system. The considered system model, which consists of a differential-algebraic equation system, was adapted from the literature. All simulations were performed using libraries developed by the author, based on methods from the Scipy and Assimulo libraries. A reference steady state was obtained for the design conditions, and continuous-time transfer functions were identified from step response data. The identified models were used in a predictive controller, and closed-loop simulations were performed to evaluate the controller tuning. In the sense of prognostics, a stochastic model of multiphase pump degradation, sensitive to the process operating condition, was proposed, and a particle filter was implemented to perform online degradation state estimation and remaining useful lifetime prediction. At last, a health-aware controller was designed, and some difficulties in combining reference tracking and lifetime extension objectives were investigated. The obtained results indicate that dealing with the health-aware control problem through the multiobjective optimization theory and addressing the useful lifetime extension in an optimization layer may result in more satisfactory results.