Iterative Learning Control for High-Speed Rosette Trajectory Tracking
- Resource Type
- Conference
- Authors
- Nikooienejad, Nastaran; Maroufi, Mohammad; Reza Moheimani, S. O.
- Source
- 2019 IEEE 58th Conference on Decision and Control (CDC) Decision and Control (CDC), 2019 IEEE 58th Conference on. :6832-6837 Dec, 2019
- Subject
- Aerospace
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Nanopositioning
Harmonic analysis
Damping
Adaptive control
Micromechanical devices
Iterative learning control
Trajectory
- Language
- ISSN
- 2576-2370
We demonstrate high-speed tracking of a self-repeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace the sum of two sinusoids with different frequencies but identical amplitudes. An iterative learning controller (ILC) is combined with a feedback controller to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies while the ILC is employed to eliminate the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two-degree-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 38 % owing to the ILC.