Feedforward

Prime #

862

Origin domain

Engineering & Design

Subdomain

control and information systems → Engineering & Design

Core Idea

A predictive model of an action's consequences is interposed upstream of irrevocable commitment, so the actor pre-corrects rather than waits for a deviation to feed back. Where feedback corrects realized error, feedforward opens a window of cheap anticipatory correction.

How would you explain it like I'm…

Catch It Early

When you reach to catch a ball, you don't wait until it hits your hand — you guess where it's going and move there ahead of time. Feedforward is using a good guess about what will happen next, so you can get ready before it actually happens instead of fixing it afterward.

Brace Before the Bump

Imagine you're carrying a tray and you see someone about to bump you. You can wait until they hit you and then stumble to recover (that's reacting after the fact), or you can brace yourself a second before the bump using your guess of what's coming. Feedforward is that second thing: you act on a prediction of what an action will cause, before you fully commit, so you can correct ahead of time. There's usually still a backup that catches whatever your guess got wrong. It works because a good prediction is often much cheaper than cleaning up a mistake.

Predict-Then-Act

Feedforward supplies predictive information about the consequences of an action before the action is committed, so the actor pre-corrects instead of waiting for an error. Contrast it with feedback, which closes a loop after the output is realized — sense the deviation, then adjust. Feedforward instead uses a model of what the action will produce, shifting correction from the reactive arc to the anticipatory arc. Every feedforward setup has four parts: an actor with an action ready but not yet committed, a disturbance or consequence that can be anticipated, a predictive model mapping intended action and disturbance to expected outcome, and a channel to adjust the action before it's committed. A residual feedback loop usually remains to catch what the model missed.

 

Feedforward is the structural arrangement in which a system supplies predictive information about the consequences of an action before the action is committed, so the actor can pre-correct rather than wait for a deviation to feed back. Where feedback closes a loop after output is realized — sense the error, then adjust — feedforward opens a window of cheap pre-commitment correction based on a model of what the action will produce, shifting correction from the reactive arc to the anticipatory arc. The essential commitment is that a predictive model is interposed between intention and irrevocable commitment: the actor acts on the modeled consequence rather than the realized one. Every feedforward arrangement specifies four elements: an actor with an action available but not yet committed, a measurable or modelable disturbance or consequence, a predictive model mapping intended action and disturbance to expected outcome, and a pre-action correction channel. A residual feedback loop typically remains, catching whatever the model missed. The pattern is licensed by a cost asymmetry: modeling the consequence before acting is often vastly cheaper than the realized error it averts, and the substrate of the model is incidental.

Broad Use

• Control engineering: A feedforward controller measures an upstream disturbance and pre-sets the actuator before the controlled variable drifts.
• Human-computer interaction: Previews, dry-run modes, and "this will delete 37 files" dialogs let a user predict the outcome before committing.
• Organizational planning: Pre-mortems, impact statements, and budget projections model downstream consequence before resources are committed.
• Training: A worked example or simulator run shown before the attempt shifts error cost from recovery to pre-commitment.
• Neuroscience: Efference-copy and forward-model circuits predict the sensory consequences of an intended motor command.
• Software operations: A deployment dry-run pre-corrects while monitoring catches the residual.

Clarity

It separates two look-alike questions calling for opposite interventions — what happened? (feedback) versus what will happen if I do this? (feedforward) — so a latency problem can be eliminated by prediction rather than faster reaction.

Manages Complexity

It splits the disturbance along a clean seam: measurable disturbances are pre-corrected by an open-loop model while unmeasurable residuals are left to feedback, turning one problem into the sum of two simpler ones.

Abstract Reasoning

It exposes an information-cost asymmetry — modeling a consequence before acting is often far cheaper than the realized error — while gating the move on a sharp test: is the model accurate enough that pre-correcting beats not correcting?

Knowledge Transfer

• Control to HCI: A pre-set actuator and a destructive-action preview are the same upstream model placed before commitment.
• Control to governance: A feedforward term on a measured disturbance and a pre-mortem on anticipated risk share one loop topology and one accuracy caveat.
• Engineering to neuroscience: Efference copy is the brain's forward model, pre-tuning an actuator exactly as a controller does.

Example

A heat exchanger senses inlet temperature upstream and pre-sets the steam valve from an energy-balance model before the cold slug reaches the transfer zone, cancelling the disturbance in anticipation while a residual feedback loop trims what the model missed.

Not to Be Confused With

• Feedforward is not Feedback because it corrects before commitment using a model of the consequence, whereas feedback corrects after a deviation is realized.
• Feedforward is not Prediction because it is the structural placement of a model upstream of action, whereas a forecast that arrives after commitment is prediction without feedforward.
• Feedforward is not Learning because it uses a model to pre-correct, whereas learning revises the model from experience.