Practical Control of Surge Tanks Suffering from Frequent Inlet Flow Upsets

Abstract

In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented. Abstract: In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented.

Advanced Regulatory Control Techniques for Improved Averaging Level Control Performance

“…P-only level control , is a commonly used form of averaging level control found in industry. Typically, P-only control is done in one of two ways.…”

“…These moves will be made until the level limit is reached, and the level is balanced. Optimal averaging level control has been implemented and tested widely, and it is accepted that it improves averaging level control performance. ,,,,,,− …”

“…Performance metrics found in the literature typically only penalize movement of u while assuming that the level does not violate the preset limits. These include the standard deviation of u (σ u ) ,, and the total variance of u (TV) where N is the number of data points in the data set and μ is the mean of u over the data set.…”

“…Performance metrics found in the literature typically only penalize movement of u while assuming that the level does not violate the preset limits. These include the standard deviation of u (σ u ) ,, and the total variance of u (TV) σ u = 1 N − 1 Σ k = 2 N false[ ( u k − u k − 1 ) − μ false] 2 TV = Σ k = 1 N | u k + 1 − u k | where N is the number of data points in the data set and μ is the mean of u over the data set.…”

“…Averaging level control is important for the stability of processing plants and is widely studied in the literature. Techniques in the literature include proportional-integral-derivative (PID) control, − piecewise-linear (e.g., gap) control, ,, range control, nonlinear PID-based control, ,,, nonlinear control, − optimal control, ,,− and model-based control. ,,− …”