Cross-coupled iterative learning control of systems with dissimilar dynamics: Design and implementation

Kira L. Barton, David J. Hoelzle, Andrew G. Alleyne, Amy J Wagoner Johnson

Research output: Contribution to journalArticlepeer-review


Cross-coupled iterative learning control has previously been applied to contour tracking problems with planar manufacturing robots in which both axes can be characterised as similar systems; having similar dynamics and identical hardware. However, there are many repetitive applications in which dynamically dissimilar systems cooperate to pursue a primary performance objective. This article introduces a novel framework to couple dynamically dissimilar systems while applying iterative learning control, showing the ability to noncausally compensate for a slow system with a fast system. In this framework, performance requirements for a primary objective can more readily be achieved by emphasising an underutilised fast system instead of straining a less-capable slow system. The controller is applied to a micro-robotic deposition manufacturing system to coordinate a slow extrusion system axis and a fast positioning system axis to pursue the primary performance objective, dimensional accuracy of a fabricated part. Experimental results show a 14% improvement in fabrication-dimensional accuracy with only marginal changes in actuator effort, as compared to independently controlled axes.

Original languageEnglish (US)
Pages (from-to)1223-1233
Number of pages11
JournalInternational Journal of Control
Issue number7
StatePublished - Jul 2011


  • coupled systems
  • cross-coupled control
  • dissimilar dynamics
  • Iterative learning control
  • manufacturing applications
  • micro-robotic deposition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


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