Adaptive feedback linearizing control of a gas liquid cylindrical cyclone

Abstract

As subsea production of oil and gas reaches deeper and more remote waters, the need for more compact separation equipment arises. The gas liquid cylindrical cyclone (GLCC) is a widely used separation device in topside facilities, but has yet to reach the same popularity subsea. The GLCC separates gas and liquid by inducing a swirl on the multiphase flow. Because of its small size, the GLCC is sensitive to flow variations which may reduce separation performance. The performance of the GLCC can be improved by control. In this paper we consider a nonlinear dynamic model of a GLCC containing unmeasured variables and states. We present an adaptive feedback linearizing controller and prove that the origin of the gas pressure and liquid level error systems are locally asymptotically stable in the sense of Lyapunov on a specified domain. The model and controller are implemented in Simulink and simulations show that the controller works very well, even with uncertainties in assumed known parameters, and measurement noise.

State and Parameter Estimation for a Gas-Liquid Cylindrical Cyclone

“…Offset-free control of the controlled variables h L and p G is achieved by augmenting the transformed state vector (9) with two integral error states of the controlled variables.…”

“…The last group of (advanced) controllers typically require a model of the plant and therefore, they achieve both (feedback and feedforward) control of the measured variables and optimization based on unmeasured variables (e.g. [7], [8], [9], [10] and [11]). Information of these unmeasured variables are only available through estimation and require the development of estimators.…”

Robust adaptive backstepping DP control of ROVs

“…The other damping parameters in North, East and Heading and the estimated disturbances are not drifting or otherwise suffering from the influence of measurement noise, i.e., the applied Extended Kalman Filter is doing a sufficient job in filtering the measured signals. The presence of this drift, however, implies that a projection operator that ensures that the parameters stays within predefined bounds should be applied in the future (Ohrem et al, 2017).…”

Controller Design and Control Structure Analysis for a Novel Oil–Water Multi-Pipe Separator

“…Furthermore, model reference adaptive control is applied to a pipe separator. Adaptive control schemes have seen applications in process control [12] and offshore oil and gas production [13][14][15], but the authors have not been able to locate any prior published work on adaptive control of pipe separators.…”