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Iterative Learning Control (ILC)

Design Features

  • Optimizes your part profile
  • Increase throughput
  • Eliminate tracking error
Figure 1. Example of improving position error through iterative learning control.

Increase Throughput and Eliminate Tracking Error

ILC is an advanced feature which examines the following error from previous trajectory runs and then calculates an optimal commanded trajectory such that the desired part geometry is achieved. After you run the trajectory a number of times, the iterative algorithm optimizes the position tracking. Each time that you run the trajectory with learning control enabled, ILC collects and uses the information to optimize the trajectory to achieve near-zero following error.

A typical ILC optimization starts out with significant Position Error (PosErr) and a smooth Acceleration Command (AccCmd) profile.

Figure 2. Plot of position error relative to acceleration command before iterative learning control is implemented.

After 10 learning runs, the Position Error is nearly eliminated and you can see a change in the Acceleration Command. This updated motion trajectory minimizes the following error.

Figure 3. Tremendous improvements in positioning error are realized after 10 learning runs. Acceleration command is changed from Figure 2 to achieve the improved positioning error.

Iterative Learning Control is a feature in Aerotech’s Motion Designer software package and available for:

  • A3200 Software-Based Machine Controller
  • Ensemble Stand-Alone Multi-Axis Motion Controller
  • Soloist Stand-Alone Single-Axis Motion Controller

Applications

  • Electronics Manufacturing
  • Laser Processing
  • LED Display Manufacturing
  • Research Systems
  • Semiconductor