This paper presents an improved method for precision motion control by combining Iterative Learning Control (ILC) and Cross-Coupled Control (CCC) in a novel way that improves overall tracking performance. Previous developments in precision motion control have introduced a CCC feedback method which results in improved contour error. Contour error is a nonlinear combination of the individual axis tracking errors . In this paper, ILC and CCC are combined to overcome limitations present in each technique. In this new method, multi-axis CCC is reformatted into a single-input single-output (SISO) ILC approach, in which learning of the cross-coupled error leads to a modified control signal and subsequent improvements in the trajectory tracking performance. This approach is different from multi-input multi-output (MIMO) ILC  approaches in that two non-coupled systems are combined into one nonlinear system in which the coupling is introduced through only the error dynamics. In this paper, sufficient stability and convergence properties are given for the proposed algorithm. A design for a Cross-Coupled ILC (CCILC) system is presented, and the performance of this system is compared to the performance of existing control systems. Computer simulation and experimental testing of this design are implemented on a microscale robotic deposition (μ - RD) system  to assess the overall performance benefits. It is shown through simulation and experimental testing that combining CCILC with individual axis ILC produces the greatest overall performance improvement by capitalizing on the gains acquired from each technique.