Posts Tagged ‘Final Control Element’
When Cascade Control Isn’t the Right Solution
Sometimes looking for the right answer can be difficult especially within the realm of process control. While it can be easy to identify solutions that satisfy some requirements it can often be a challenge to find options that meet multiple success criteria. Something usually has to give. Indeed, sometimes it’s easier to consider the reasons not to do something. Applying a philosophy of ‘no’ can be particularly helpful when considering Cascade Control.
Read MoreThe Pros and Cons of Cascade Control
As shared previously Cascade Control is an advanced application of Single Loop Control. Through the use of a secondary and faster PID control loop, practitioners can improve a given process’ ability to correct for known disturbances. Although it is considered an advanced strategy, Cascade Control is commonly used across the process industries.
Read MoreOverview of Cascade Control
While Cascade Control is generally considered an advanced control strategy, it is only marginally more complex to implement than Single Loop Control. More often than not it is applied to improve the performance of a slow process such as temperature that demonstrates sluggish behavior. Essentially Cascade Control improves a “slow” control loop’s ability to respond to disturbances by capitalizing on the dynamics of a faster one – something quicker like a flow or a pressure loop. The faster loop provides an early warning variable that facilitates disturbance rejection, helping to maintain steady performance of the slower primary loop.
Read MoreHow to Perform a Step Test
Tuning PID controllers is a multi-step process. While it is important to understand each step in the process, performing the bump test and collecting dynamic data is the most crucial step that generally dictates the outcome. This post delves into one particular type of test – the Step Test – before introducing other tests commonly used in PID controller tuning.
Read MoreData Collection Speed is Key to the Accurate Interpretation of Process Dynamics
If you’re old enough to remember silent movies, then you know what it’s like to see the characters seemingly jiggle around the screen. Black spots would randomly appear as the story was told with the help of subtitles. Spots and subtitles aside, these movies appeared jittery due to their slow speed. The slow frame rate – a precursor of data collection speed – resulted in visual gaps.
Read MoreUsing Percent Time in Normal to Uncover Tuning Issues
Even Simple Metrics Such as Percent Time in Normal Reveal Issues that Negatively Affect Performance and Signal the Need for Controller Tuning
It’s easy to get tripped up if a shoelace is untied. Just ask any child. While that’s a lesson most learn early in their lives each of us can occasionally slip up and find ourselves at risk.
Read MoreUsing the Oscillation Metric to Uncover Tuning Issues
There’s a wealth of information available in most every data historian. The data can be used to evaluate the performance of a plant’s regulatory control systems in general and to uncover PID controllers that require tuning in particular. Capitalizing on that resource can help manufacturers keep their processes within designated constraints and avoid out-of-spec production.
Read MoreCommon Industrial Applications of PID Control with Filter
Other Questions.
Sometimes controller design feels like a choice between the lesser of not two but three evils. P-Only Control is simple and provides a fast response, but the resulting Offset hinders tight control. PI Control addresses Offset but it leaves room for improvement. And then there’s PID Control which enhances a loop’s Set Point Tracking but typically at the expense of the associated Final Control Element (FCE). If not for the ubiquitous nature of noise in industrial applications, then PID Control would be the clear choice. But since there’s no escaping noise, what’s a practitioner to do?
Common Industrial Applications of PID Control
A previous post about the Derivative Term focused on its weaknesses. As noted, the primary challenge associated with the use of Derivative and PID Control is the volatility of the controller’s response when in the presence of noise. Noise is a major stumbling block for Derivative and PID Control as production data is routinely replete with process noise and other sources of variability. The use of PID Control in such an environment can drive frenetic changes in a loop’s Controller Output (CO) and unnecessarily wear out the associated Final Control Element (FCE). In summary: Little to gain; lots to lose.
Read MoreHow Can I Correct for Noise Using External Filters?
Choices, choices. In the realm of process control practitioners are regularly forced to choose between competing options. Consider a PID control loop: Should it be tuned for faster disturbance rejection or tighter Set Point tracking? Should the Derivative Term be used or does the PI configuration provide a sufficiently fast Settling Time? And the choices go on and on. In that sense there are multiple choices for filtering noise too – options that provide very different benefits. Fortunately when it comes to filtering for Signal Noise the choice is typically clear.
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