How Do I Tune a Level Controller?

Level is Among the More Common Industrial Control Loops…and Among the More Misunderstood

Level controllers present challenges that are different from others. Although their presence is significant they lag behind Flow controllers in their overall share of the typical production facility’s process control landscape. Unlike other processes such as Temperature, Pressure and Flow, Level control loops demonstrate different dynamics, they don’t play by the same rules as the non-integrating (also known as self-regulating) types. And although best-practices for modeling and tuning Level loops are similar they involve nuances that can hamper a less experienced practitioner.

Below are several important considerations to keep in mind when tuning a Level control loop:

  • Know The Objective

First and foremost it’s essential that a given PID loop’s control objective is understood clearly. Two common objectives for Level control are Set Point tracking and disturbance rejection. Set Point tracking generally involves conservative tuning so that variability within the loop itself is minimized. In contrast, disturbance rejection seeks to minimize downstream variability through the use of fast responding, aggressive tuning. A third objective with broad industrial application is controller smoothing. The Level controller’s responsiveness is muted relative to variability in the process, allowing for effective control of wild streams without excessive wear and tear on pumps and other instrumentation.

If the loop’s purpose is vague, then investigate the situation further lest things get out of hand after the tuning procedure is completed. Automation history is replete with stories of control loops that were tuned with the wrong objective in mind. More often than not those stories didn’t end well.

  • Keep an Open Mind

Although Level loops can be tuned in either open- or closed-loop, their characteristics are such that open-loop testing is typically more expedient. Like other integrating or non-self-regulating processes, Level loops do not naturally settle at a new operating state when a change to the associated Controller Output (CO) is made. Rather, they tend to drift steadily (whether up or down) until the original CO value is restored. As a result closed-loop testing is often impractical as it either requires Set Point changes that are excessive or fails due to oscillatory behavior.

Open-loop testing of Level generally provides quality data with which to model the process’ dynamics. A steady-state is not required before testing is initiated. What is needed, however, is a shift in the CO to two different and constant values, one above and another below the initial operating value. As the Process Variable (PV) responds to each of the two values their slopes can be determined and used in calculating Integrator Gain. The Dead-Time can usually be determined simply by noting the delay in the PV’s response following the second CO shift.

  • Timing is Everything

Once a Level loop’s dynamics are accurately modeled the next step is to apply tuning correlations and calculate parameters for use with the PID controller. A wide array of correlations exist. Internal Model Control (IMC) correlations with their use of the Closed-Loop Time Constant (CLTC) generally provide robust control that enhance stability, a good thing with integrating processes like Level. Best practice is for the CLTC value to be as large as possible while fast enough to arrest or recover from a major disturbance.

Calculating tuning parameters involves higher order math and can be tricky so be sure to check your work. What’s more, test the new tuning parameters and confirm that the loop delivers the type of performance required for safe and effective Level control.

Although Level loops have unique attributes, establishing effective control over them is an essential step towards improved process control performance. Whether or not you choose to use the IMC tuning (i.e. Lambda tuning) correlations, the same considerations outlined above apply.

If you are interested in PID controller tuning techniques, download our PID Tuning Guide for simplified loop tuning guidelines. The guide offers proven and repeatable methods for diagnosing and optimizing underperforming PID controllers.  If you’re interested in more in depth coverage of the PID controller, enroll in our 2-day Practical Process Control training and skills development workshop.

These resources offer related content:

What is On-Off Control?

On-Off Control Has a Role to Play in Industrial Automation…But Within Limits On-Off Control is not a highly sophisticated control method. Even so, examples of its practical, everyday use can be found all around. Look no further than the appliances in your home. Kitchen appliances...
Digital,City,Series.,Arrangement,Of,Three,Dimensional,Fractals,And,Numbers

Marginal Process Performance Gains Can Add Up Fast

Looking for areas to improve production may seem overwhelming. There are countless factors, inputs, and outputs to consider and analyze. It’s typical for staff to limit their focus only to projects with the potential of significant gains. Ironically, that’s not always the best approach. Multiple...
shutterstock_1938620782 (1)

PI Asset Framework: A CLPM History Lesson

When does History matter? Well, in 2017 OSIsoft introduced Control Station as a valued member of the Partner EcoSphere. At the time Control Station’s PlantESP was the first control loop performance monitoring (CLPM) solution to integrate seamlessly with the PI System using the PI SDK....

Still looking for more?

Now that you’ve gotten the basics, connect with our team to learn how our people, processes and technologies can help you optimize.