Cross Coupled Iterative Learning Control (CCILC) has previously been applied to contour tracking problems with planar robots in which both axes can be characterized as similar systems; having similar dynamics and identical hardware. However, there are many repetitive applications in which dissimilar systems cooperate to pursue a primary performance objective. This paper introduces a novel framework to couple dissimilar systems while applying Iterative Learning Control (ILC), 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 emphasizing an underutilized fast system instead of straining a less-capable slow system. The controller is applied in simulation and experimentally to a micro-Robotic Deposition (μRD) 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 30% improvement in fabrication dimensional accuracy with only marginal changes in actuator effort in the slow system, as compared to independently controlled axes.

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