Applying Adaptive Control to Difficult Level Control Applications

As we get further away from our college years, sometimes misconceptions can solidify. For instance, most engineers that had a basic control theory class may recall that increasing the gain in a feedback loop at some point will introduce instability/oscillations. The misconception is that this is not universally true for all loops, such as level loops.

ModelingAndControl.com‘s Greg McMillan has a great article co-developed with researchers at India’s MIT Anna University on ControlGlobal.com, Adaptive Level Control: Exploring the Complexities of Tuning Level Controllers and How an Adaptive Controller Can Be Used in Level Applications. Greg, Sridhar Dasani and Dr. Prakash Jagadeesan clear up the gain misconception:

…the opposite correction is more likely needed for integrating processes. Most level loops are tuned with a gain below a lower gain limit. We are familiar with the upper gain limit that causes relatively fast oscillations growing in amplitude. We are not so cognizant of the oscillations with a slow period and slow decay caused by too low of a controller gain. The period and decay gets slower as the controller gain is decreased. In other words, if the user sees these oscillations and thinks they are due to too high a controller gain, he or she may decrease the controller gain, making the oscillations worse (more persistent).

The authors describe some challenging level control applications such as continuous reactors, crystallizers, and material balances in unit operations that require extremely tight level control. For process vessels such as horizontal tanks, drums, and spheres, the level change for a given flow rate is not linear because of the geometry of the vessel. Changes in the fluid density and use of non-linear valves can also increase the challenge to perform tight level control.

The authors note that adaptive level controls, built on adaptive control software such as DeltaV InSight, can

…not only account for the effect of vessel geometry, but also deal with the changes in process gain from changes in fluid density and nonlinear valves. Even if these nonlinearities are not significant, the adaptive level control with proper tuning rules removes the confusion of the allowable gain window, and prevents the situation of level loops being tuned with not enough gain and too much reset action.

The article highlights process dynamics related to conical tanks. These tanks have extreme changes in cross sectional area as the level changes. The MIT Anna University research lab used the embedded DeltaV InSight software to automatically identify the process dynamics around changes to the level setpoint within the conical tank. The authors describe how this is done:

The adaptive controller employs an optimal search method with re-centering that finds the process dead time, process time constant, and process gain that best fits the observed response. The trigger for process identification can be a setpoint change or periodic perturbation automatically introduced into the controller output or any manual change in the controller output made by the operator.

The article is complete with equations for integrating process gains, conical tank dynamics, and controller tuning rules. These may help awaken those brain cells if you’re like me and have let these cells remain dormant over the past several years.

The authors summarize their findings:

Adaptive level controllers can eliminate tuning problems from the extreme changes in level control dynamics associated with different equipment designs and operating conditions. The integrated tuning rules prevent the user from getting into the confusing situations of upper and lower gain limits and the associated fast and slow oscillations. The smoother and more consistent response allows the user to optimize the speed of the level loop from fast manipulation of column reflux and reactor or crystallizer feed to slow manipulation of surge tank discharge flow control.

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