Feedforward¶
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
Brace Before the Bump
Predict-Then-Act
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.
Relationships to Other Abstractions¶
Current abstraction Feedforward Prime
Parents (1) — outgoing typed relations
-
Feedforward includes Representation Prime
Feedforward contains a predictive representation mapping intended action and disturbance to expected consequence before commitment.
Children (3) — abstractions linked here by typed relations
-
Egain forecasting Domain-specific is a kind of Feedforward
It remains its own entry because its identity is fixed by the building zone and thermal model, weather inputs and horizon, measured state, occupancy and comfort target, heat-system constraints, forecast update, control action, calibration and performance evidence.
-
Predictive Remapping Domain-specific is a kind of Feedforward
Predictive remapping is feedforward compensation specialized to using an efference copy to shift a visual representation before an impending saccade changes its input coordinates.
-
Digital Room Correction Domain-specific includes Feedforward
A measured playback-path model informs correction before acoustic output occurs.
Hierarchy path (1) — routes to 1 parentless root
- Feedforward → includes Representation → presupposes Abstraction
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.