Iterative Learning Controller Based on Linear Extended State Observer for Six-Degree-of-Freedom Micro-Motion Stage

In order to achieve high-performance trajectory tracking of the 6-DOF micro-motion stage (6-DOF MMS) and effectively mitigate the crosstalk issue caused by incomplete decoupling and thrust fluctuation problem of the voice coil motor, an iterative learning control (ILC) based on linear extended State Observer (LESO) is proposed. The frequency domain error analysis of the proposed algorithm is realized by utilizing LESO as a DOB equivalent in the time-domain. The introduction of LESO enables observation and compensation for model uncertainty and low-frequency disturbance within the observer's bandwidth, reducing initial tracking error and thereby enhancing both convergence speed and accuracy of ILC. Moreover, it improves system robustness against non-repetitive interference while eliminating repeated tracking errors. Simulation and experimental results validate the effectiveness of the proposed control scheme.