Slug Detection As a Tool for Predictive Control of GLCC© Compact Separators

Abstract

Abstract Current design and performance of the GLCC©1 separator is dependent on the prediction of the upstream inlet flow conditions based on available models. It is expected that early detection of terrain slugging (slug length, slug velocity and holdup) and controlling the liquid level in the GLCC using feed forward mechanism can improve the operational range of GLCC, by decreasing the gas carry under and liquid carry over, and thereby decreasing the control valve dynamics. The conventional feedback control loops can seldom achieve perfect control considering the impact of huge slugs that are keeping the output of the process continuously away from desired set point value. The reason is simple: a feedback controller reacts only after it has detected a deviation in the value of the level from the set point. Unlike the feedback systems, a feed forward control configuration measures the disturbance directly and takes control action to negate the effect of the disturbance on liquid level in the GLCC. Therefore, feed forward control system has the theoretical potential for perfect control if the slug detection and characterization are accurate. A strategy for GLCC predictive control has been proposed which integrates the feedback and feed forward loops to compensate for error due to modeling and slug characterization. A model has been developed for predictive control system design and simulated in MATLAB-Simulink®. Experimental results obtained demonstrate that the proposed strategy is a viable approach for GLCC predictive control.