Design and Analysis of A Modular Learning Based Cross-Coupled Control Algorithm for Multi-Axis Precision Positioning Systems

Increasing demand for micro/nano-technology related equipment resulted in growing interest for precision positioning systems. In this paper a modular controller combining cross-coupled control and iterative learning control approaches to improve contour and tracking accuracy at the same time is presented. Instead of using the standard error estimation technique, a computationally efficient and modular contour error estimation technique is used. The new controller is more suitable for tracking arbitrary nonlinear contours and easier to implement to multi-axis systems. Stability and convergence analysis for the proposed controller is presented with the necessary conditions. Effectiveness of the control design is verified with simulations and experiments on a two-axis positioning system. The resulting positioning system achieves nanometer level contouring and tracking performance.