High-Performance Tracking of Piezoelectric Positioning Stage Using Current-Cycle Iterative Learning Control With Gain Scheduling

In this paper, two types of sampled-data current-cycle iterative learning control (ILC) (CILC) schemes are exploited to perform high-performance tracking control for piezoelectric positioning stage systems. The proposed CILC schemes consist of a direct feedback control (FC) loop and an add-on ILC loop and thus can simultaneously deal with repeatable and nonrepeatable components in tracking error. Based on the modeling result of the control system, gain-scheduling technique is further incorporated in the learning filter design of the ILC loop to speed up the learning convergence. In consequence, low tracking error in the time domain and fast convergence speed in the iteration domain are achieved concurrently. In the end, to illustrate the respective characteristics of CILC schemes and verify their superiorities to pure FC or pure ILC, a set of experiments including low-frequency (2 Hz) tracking and high-frequency (100 Hz) tracking is conducted with detailed comparisons among proportional/proportional-plus-integral control, pure ILC with robust design, pure ILC with gain scheduling, and CILC with gain scheduling.

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