What is Feed Forward Control?

To no practitioner’s surprise, process control exists as a discipline because manufacturing is complex.  It’s erratic and occasionally unpredictable.  At many facilities it is highly hazardous.  Variability – whether localized to a single process or reverberated throughout a plant – can transform production from a well-managed operation to a highly turbulent task.  Variability is a key reason why manufacturing is difficult.  So it’s no wonder that process engineers focus their efforts on controlling disturbances – those unplanned upsets which drive variability from one process to the next.

Cascade Control was previously covered as an advanced architecture for improving a process’ ability to reject disturbances.  Feed Forward is another advanced schema that is widely used in industry to overcome the limitations of traditional feedback control.  While both Cascade and Feed Forward Control involve additional instrumentation and engineering time, Feed Forward is different in that it is applied to a downstream process that is often distant from the source of disturbances.  Feed Forward proactively corrects for those disturbances by anticipating the timing and size of their impact…and by not waiting for the PID’s normal, measured response to Error.

As with other topics covered on this blog there are usually a few key points to keep in mind.  In terms of the basics of Feed Forward Control it would be helpful to take the following points into consideration:

Single Out the Source

A process that experiences variability due to frequent, upstream load changes is a good candidate for Feed Forward.  By being frequent it’s assumed that the disturbance is readily identifiable and can be modeled.  Similarly, by being upstream it’s reasonable to think that there is a measurable period of time between the disturbance and its downstream impact.  The ability to single out the source of the problem is essential to a successful Feed Forward implementation.

Model the Dynamics

Metaphorically, for every punch delivered by a load change or other upstream upset the Feed Forward architecture delivers an accurately timed and sized counter-punch.  In order for Feed Forward to do an effective job an accurate disturbance model must be calculated.  The model must account for a full spectrum of upsets – those ranging in size from small and insignificant to large and overwhelming.  By modeling the dynamics of the disturbances’ varying magnitude the Feed Forward architecture can deliver an appropriately measured response without waiting for Error to grow.

Timing is Everything

If a known disturbance’s effect on the process is immediate, then Cascade Control may be the right solution for the job.  However, if the process can’t wait for the PID to first see then respond to Error, then that is where Feed Forward control provides unique value.  By accounting for the disturbance’s full impact Feed Forward assures that adjustments are made precisely at the right time – it doesn’t adjust the controller prematurely and inadvertently harm the process.  Timing as with most things in life is everything.

Like Cascade, Feed Forward does not affect a process’ ability to track Set Point.  Even so it is a meaningful disturbance rejection strategy that capitalizes on capabilities within the PID controller.

These resources offer related content:

info overload

Fewer Metrics Leads to Better Results

Big Data and IIoT have captured the automation industry’s imagination. A key take-away from all that’s been written is that plant data holds the key to making many production processes safer, more efficient, and more profitable. While there’s growing evidence that Big Data and IIoT...

What is Lambda Tuning?

Adjusting a Single Tuning Parameter for Optimal Control Loop Performance Tuning a PID controller should always start with a clear understanding of both the control objective and the Design Level of Operation (DLO).  Unfortunately a subsequent step (the calculation of tuning parameters) can often put practitioners...

Pros and Cons of Higher Order Models

Modeling is a time-tested approach for decoding a process’ dynamic behavior.  By understanding how a process responds to change it’s possible to apply an appropriate and timely counter measure.  Two common applications of modeling are 1) PID controller tuning, and 2) process simulation. There are...

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.