Iterative Learning Control using a basis signal library

Abstract

There are a vast number of manufacturing applications that are repetitive in nature and therefore can benefit from Iterative Learning Control (ILC) algorithms. However, some of these applications are unfit for continuous open loop signal updates from ILC either because the complete manufacturing cycle includes abrupt transitions in system dynamics or is prohibitively long for efficient implementation. This paper explores a method to control one such system, Micro Robotic Deposition (μRD), using ILC as an open loop control signal identification technique. Instead of continuously updating the ILC control signal for the complete operation, we exploit the characteristic that all μRD cycles are a sequence of a few basis tasks and only these basis tasks are learned. Control signals for these basis tasks build a library of basis signals, which can then be appropriately sequenced as the control signal for the complete manufacturing cycle. This paper introduces a method to build this basis signal library and extract and coordinate the signals depending on predefined μRD operations and material used as specified by numerically controlled machine language. The methods applied to μRD display the ability to drastically improve end product quality with a significantly shortened signal identification process.