Feed-forward control: A proven scheme for rejecting disturbances
If we’re being honest, then let’s acknowledge that the PID and feedback control have limitations, especially when lag is involved.
The strength of the PID rests largely in the breadth of industrial applications for which it provides safe, stable control. And while many in industry might argue that the PID is difficult to configure, there seems to be an equal share of practitioners who view PID controller design and tuning as a relatively intuitive process. Where there seems to be nearly unanimous agreement is in the PID’s weaknesses. Chief among the complaints is the PID’s challenges when it comes to correcting for persistent disturbances. Fortunately for the many industrial users of PID, there’s feed-forward control.
Figure 1: Processes that are slow-moving or that exhibit long dead times can benefit the most from feed-forward control.
Feed-forward control – or more simply, "feed forward" – is an advanced control scheme that builds upon basic PID control and enables practitioners to overcome the challenges of rejecting disturbances. More specifically, feed forward employs a secondary model of a known disturbance. Whereas a simple PID will wait for disturbances to make their impact, feed forward’s additional disturbance model allows it to respond proactively to disturbances in terms of timing and magnitude. Essentially, the feed-forward element uses a disturbance model to predict an impact profile (how far and fast the process variable will move in response to the disturbance), and then it uses a process model to determine how much it would need to adjust the controller output to completely counteract the disturbance.
As with most topics related to PID and process control, there are a few key points to keep in mind. In terms of feed-forward control, the following are worth considering:
- Isolating the source - Feed-forward is a good solution when a given process is routinely affected by a known and measurable source of disturbances. One example would be a semi-continuous oven whose doors are opened every 15 minutes to push new material in and out of the system. Such changes are typically sizable, and they have a significant impact on the temperature of the oven. Because of the frequency of events such as load changes, it's likely that the source can be isolated and the disturbance’s dynamics can be modeled. Not for nothing: It is absolutely essential that a practitioner can isolate and measure the disturbance source. If that’s not possible, then feed-forward is no longer on the table as a suitable solution.
- Modeling the disturbance - The impact of some disturbances can be profound in terms of their effect on quality, throughput, efficiency, and the like – a metaphorical punch to the gut of a process. In such situations, feed-forward serves as the counterpunch, neutralizing each disturbance proactively with an accurately timed and sized adjustment. Feed-forward relies on an accurate model of the disturbance to respond appropriately to those upsets. The model must account for a full spectrum of disturbance scenarios – those ranging in size from small and insignificant to large and overwhelming.
- Delivering on time - At the heart of the problem is the PID’s inability to correct proactively for those disturbances that are generally characterized by a significant dead time. As with many things in life, timing is everything. It is feed-forward’s use of a disturbance model that allows it to calculate the precise size and timing of a countermeasure. This feed-forward feature protects the process from major upsets while the PID responds to the usual variability within the process.
For sure, feed-forward is an effective disturbance rejection solution with broad application value. In particular, its ability to proactively correct for disturbances makes feed-forward ideal for processes that experience frequent and measurable load changes. It enhances the capabilities of basic feedback control as provided by the PID.
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About the Author
Alexis GajewskiAlexis Gajewski
Senior Content Strategist
Alexis Gajewski is a manufacturing writer and editor with nearly 20 years of experience covering the people, practices, and technologies that keep industrial facilities running. For more than a decade, she served as Senior Content Strategist for Plant Services, creating content for plant managers, engineers, and maintenance professionals on a variety of industrial topics.
During her tenure, Alexis worked to develop the brand’s digital strategy and helped launch and produce Great Question: A Manufacturing Podcast. She also created The Lighter Side of Manufacturing, a weekly blog that explored the inventive and sometimes humorous side of the industry.
Alexis co-founded Influential Women in Manufacturing, a recognition program that honored 49 women in its first two years, earned an industry award for Best Product Launch, and received a proclamation from Illinois Governor JB Pritzker and a commendation from U.S. Senator Tammy Duckworth.
She also led newsroom operations and development at a large media company where she set editorial standards, developed training curriculum, and helped support AI adoption for more than 150 editors across 80+ brands spanning manufacturing, industrial processing, automation, and more.
Additionally, Alexis works as a freelance writer and editor, and her areas of interest include continuous improvement, the skilled workforce, and the role of emerging technology on the plant floor.
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