What Is Feedforward Control? Predicting Robot Movements Before Errors Occur.

What Is Feedforward Control?

Feedforward control is a control method that calculates an action using a model, known inputs, or anticipated disturbances without waiting for an error to appear.

In robotics, feedforward control can help machines perform movements more accurately by accounting for predictable physical effects.

For example, a robotic arm lifting a heavy object must generate torque to oppose gravity.

A feedforward controller can estimate the required torque based on the arm's configuration and payload rather than waiting for the joint to begin falling below its intended position.

Key Takeaways

• Feedforward control calculates commands using information available before a resulting error occurs.
• It can improve movement tracking and reduce the amount of correction required from feedback controllers.
• Feedforward control depends on sufficiently accurate models or knowledge of relevant operating conditions.

How Does Feedforward Control Work?

Imagine a robot moving its arm along a planned trajectory.

The controller knows the intended position, speed, and acceleration at different points in the movement.

Using a model of the robot's dynamics, it can estimate the motor torques required to perform the trajectory.

These predicted commands are applied as the robot moves.

A feedback controller can then correct differences between the planned and actual movement.

For example, if unexpected friction causes the arm to move more slowly than intended, the feedback system can adjust the motor command.

The feedforward calculation handles predictable requirements, while feedback addresses residual errors and disturbances.

Feedforward vs. Feedback Control

The main distinction is how each method responds to information.

Feedforward control acts on predictions, commands, or measured disturbances before an output error develops.

Feedback control uses actual output measurements to identify and correct errors.

Consider a robot lifting a box.

A feedforward model might estimate the required gravity-compensation torque.

Feedback may correct the remaining error if the box is heavier than expected.

Neither approach is always sufficient by itself.

What Are Common Feedforward Applications?

Gravity compensation: Estimate torque required to support robot links and payloads.

Velocity feedforward: Anticipate commands associated with desired movement speed.

Acceleration feedforward: Account for the effort needed to accelerate components.

Disturbance compensation: Respond to measurable disturbances before they significantly affect the controlled output.

The effectiveness depends on model accuracy, actuator capabilities, and operating conditions.

What Are the Limitations?

Feedforward controllers cannot reliably compensate for everything they cannot predict or measure.

A model may assume a particular payload, but the actual object may be heavier.

Mechanical wear, friction changes, and other uncertainties can also affect performance.

This is why feedforward and feedback are often used together.

Frequently Asked Questions

Does feedforward control use sensors?

It can. Feedforward may use known commands, measured disturbances, or other information, but it does not require output-error feedback to calculate its contribution.

Is feedforward control faster than feedback?

It can anticipate predictable requirements, but overall performance depends on controller design and the physical system.

The Bottom Line

Feedforward control helps robots anticipate the commands required for movement. Combined with feedback, it can improve accuracy and responsiveness without relying entirely on correcting errors after they occur.