Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control
Abstract
:1. Introduction
2. System Description
3. Controller Design
3.1. Iterative Learning Control
3.2. Learning Function
4. Experiment Results and Analysis
4.1. Experimental Setup
4.2. Tracking Results
- (1)
- : feedback controller PID;
- (2)
- : model-based feedforward controller ZMETC;
- (3)
- : ILC which is illustrated in Figure 3.
4.2.1. Tracking Triangular Wave
4.2.2. Tracking Fourth-Order Motion Reference Trajectory
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Kunz, C. Synchrotron radiation: Third generation sources. J. Phys. Condens. Matter 2001, 13, 7499. [Google Scholar] [CrossRef]
- Yabashi, M.; Tanaka, H. The next ten years of X-ray science. Nat. Photon. 2017, 11, 12–14. [Google Scholar] [CrossRef]
- Ezquerra, T.A.; García-Gutiérrez, M.C.; Nogales, A.; Müller, A.J. Introduction to the special issue on “Applications of synchrotron radiation in polymers science”. Eur. Polym. J. 2016, 81, 413–414. [Google Scholar] [CrossRef] [Green Version]
- Frahm, R.; Richwin, M.; Lützenkirchen-Hecht, D. Recent advances and new applications of time-resolved X-ray absorption spectroscopy. Phys. Scr. 2005, 2005, 974. [Google Scholar] [CrossRef]
- Müller, O. Hard X-ray Synchrotron Beamline Instrumentation for Millisecond Quick Extended X-ray Absorption Spectroscopy. Ph.D. Thesis, Fakultät für Mathematik und Naturwissenschaften, Universität Wuppertal, Wuppertal, Germany, 2018. [Google Scholar]
- Yamazaki, H.; Matsuzaki, Y.; Shimizu, Y.; Tsuboki, I.; Ikeya, Y.; Takeuchi, T.; Tanaka, M.; Miura, T.; Kishimoto, H.; Senba, Y.; et al. Challenges toward 50 nrad-stability of X-rays for a next generation light source by refinements of SPring-8 standard monochromator with cryo-cooled Si crystals. AIP Conf. Proc. 2019, 2054, 60018. [Google Scholar]
- Richwin, M.; Zaeper, R.; Lützenkirchen-Hecht, D.; Frahm, R. Piezo-XAFS-time-resolved x-ray absorption spectroscopy. Rev. Sci. Instruments 2002, 73, 1668–1670. [Google Scholar] [CrossRef] [Green Version]
- Sergueev, I.; Döhrmann, R.; Horbach, J.; Heuer, J. Angular vibrations of cryogenically cooled double-crystal monochromators. J. Synchrotron Radiat. 2016, 23, 1097–1103. [Google Scholar] [CrossRef] [PubMed]
- Chumakov, A.I.; Sergeev, I.; Celse, J.P.; Rüffer, R.; Lesourd, M.; Zhang, L.; Sánchez del Río, M. Performance of a silicon monochromator under high heat load. J. Synchrotron Radiat. 2014, 21, 315–324. [Google Scholar] [CrossRef] [PubMed]
- Boeren, F.; Bruijnen, D.; van Dijk, N.; Oomen, T. Joint input shaping and feedforward for point-to-point motion: Automated tuning for an industrial nanopositioning system. Mechatronics 2014, 24, 572–581. [Google Scholar] [CrossRef]
- Ling, J.; Feng, Z.; Zheng, D.; Yang, J.; Yu, H.; Xiao, X. Robust adaptive motion tracking of piezoelectric actuated stages using online neural-network-based sliding mode control. Mech. Syst. Signal Process. 2021, 150, 107235. [Google Scholar] [CrossRef]
- Ming, M.; Liang, W.; Feng, Z.; Ling, J.; Al Mamun, A.; Xiao, X. PID-type sliding mode-based adaptive motion control of a 2-DOF piezoelectric ultrasonic motor driven stage. Mechatronics 2021, 76, 102543. [Google Scholar] [CrossRef]
- Bai, Y.; Hu, J.; Yao, J. Adaptive neural network output feedback robust control of electromechanical servo system with backlash compensation and disturbance rejection. Mechatronics 2022, 84, 102794. [Google Scholar] [CrossRef]
- Loof, J.; Besselink, I.; Nijmeijer, H. Automated lane changing with a controlled steering-wheel feedback torque for low lateral acceleration purposes. IEEE Trans. Intell. Veh. 2019, 4, 578–587. [Google Scholar] [CrossRef]
- Feng, Z.; Liang, W.; Ling, J.; Xiao, X.; Tan, K.K.; Lee, T.H. Integral terminal sliding-mode-based adaptive integral backstepping control for precision motion of a piezoelectric ultrasonic motor. Mech. Syst. Signal Process. 2020, 144, 106856. [Google Scholar] [CrossRef]
- Makarem, S.; Delibas, B.; Koc, B. Data-driven tuning of PID controlled piezoelectric ultrasonic motor. Actuators 2021, 10, 148. [Google Scholar] [CrossRef]
- Wang, W.; Ma, J.; Cheng, Z.; Li, X.; De Silva, C.; Lee, T.H. Global iterative sliding mode control of an industrial biaxial gantry system for contouring motion tasks. IEEE/ASME Trans. Mechatronics 2021, 27, 1617–1628. [Google Scholar] [CrossRef]
- Li, L.; Huang, W.W.; Wang, X.; Zhu, L.M. Dual-Notch Based Repetitive Control for Tracking Lissajous Scan Trajectories with Piezo-Actuated Nano-Scanners. IEEE Trans. Instrum. Meas. 2022, 71, 1–12. [Google Scholar]
- Mohammadi, A.; Fowler, A.G.; Yong, Y.K.; Moheimani, S.R. A feedback controlled MEMS nanopositioner for on-chip high-speed AFM. J. Microelectromech. Syst. 2013, 23, 610–619. [Google Scholar] [CrossRef]
- Liu, Y.; Yan, J.; Wang, L.; Chen, W. A two-DOF ultrasonic motor using a longitudinal–bending hybrid sandwich transducer. IEEE Trans. Ind. Electron. 2018, 66, 3041–3050. [Google Scholar] [CrossRef]
- Liu, Y.; Chen, W.; Liu, J.; Shi, S. A cylindrical traveling wave ultrasonic motor using longitudinal and bending composite transducer. Sens. Actuators A Phys. 2010, 161, 158–163. [Google Scholar] [CrossRef]
- Butterworth, J.A.; Pao, L.Y.; Abramovitch, D.Y. Analysis and comparison of three discrete-time feedforward model-inverse control techniques for nonminimum-phase systems. Mechatronics 2012, 22, 577–587. [Google Scholar] [CrossRef]
- Tomizuka, M. Zero phase error tracking algorithm for digital control. J. Dyn. Sys. Meas. Control 1987, 109, 65–68. [Google Scholar] [CrossRef]
- Qin, Y.; Tian, Y.; Zhang, D.; Shirinzadeh, B.; Fatikow, S. A novel direct inverse modeling approach for hysteresis compensation of piezoelectric actuator in feedforward applications. IEEE/ASME Trans. Mechatron. 2012, 18, 981–989. [Google Scholar] [CrossRef]
- Li, L.; Fleming, A.J.; Yong, Y.K.; Aphale, S.S.; Zhu, L. High performance raster scanning of atomic force microscopy using Model-free Repetitive Control. Mech. Syst. Signal Process. 2022, 173, 109027. [Google Scholar] [CrossRef]
- Liu, Y.; Li, J.; Jin, Z. Trajectory Tracking Control for Reaction–Diffusion System with Time Delay Using P-Type Iterative Learning Method. Actuators 2021, 10, 186. [Google Scholar] [CrossRef]
- Wu, M.; Yu, P.; Chen, X.; She, J. Design of repetitive-control system with input dead zone based on generalized extended-state observer. J. Dyn. Syst. Meas. Control 2017, 139, 071008. [Google Scholar] [CrossRef]
- Bazaei, A.; Yong, Y.K.; Moheimani, S.R.; Sebastian, A. Tracking of triangular references using signal transformation for control of a novel AFM scanner stage. IEEE Trans. Control Syst. Technol. 2011, 20, 453–464. [Google Scholar] [CrossRef]
- Song, F.; Liu, Y.; Shen, D.; Li, L.; Tan, J. Learning Control for Motion Coordination in Wafer Scanners: Towards Gain Adaptation. IEEE Trans. Ind. Electron. 2022. [Google Scholar] [CrossRef]
- Kim, K.S.; Zou, Q. A modeling-free inversion-based iterative feedforward control for precision output tracking of linear time-invariant systems. IEEE/ASME Trans. Mechatron. 2012, 18, 1767–1777. [Google Scholar] [CrossRef]
- Bolder, J.; Kleinendorst, S.; Oomen, T. Data-driven multivariable ILC: Enhanced performance by eliminating L and Q filters. Int. J. Robust Nonlinear Control 2018, 28, 3728–3751. [Google Scholar] [CrossRef]
- Bristow, D.A.; Tharayil, M.; Alleyne, A.G. A survey of iterative learning control. IEEE Control Syst. Mag. 2006, 26, 96–114. [Google Scholar]
- van Zundert, J.; Oomen, T. On inversion-based approaches for feedforward and ILC. Mechatronics 2018, 50, 282–291. [Google Scholar] [CrossRef] [Green Version]
- Fang, Y.; Hu, J.; Liu, W.; Shao, Q.; Qi, J.; Peng, Y. Smooth and time-optimal S-curve trajectory planning for automated robots and machines. Mech. Mach. Theory 2019, 137, 127–153. [Google Scholar] [CrossRef]
Frequency (Hz) | RMS Error (arcsec) | MAX Error (arcsec) | ||||
---|---|---|---|---|---|---|
PID | ZMETC | ILC | PID | ZMETC | ILC | |
10 | 593.28 | 57.60 | 52.56 | 779.4 | 188.64 | 116.28 |
20 | 545.27 | 91.33 | 80.02 | 1366.6 | 293.57 | 185.17 |
30 | 474.42 | 151.93 | 103.27 | 1736.4 | 560.97 | 306.14 |
Frequency (Hz) | RMS Error (arcsec) | MAX Error (arcsec) | ||||
---|---|---|---|---|---|---|
PID | ZMETC | ILC | PID | ZMETC | ILC | |
18 | 819.25 | 68.26 | 76.83 | 1581.1 | 137.38 | 142.56 |
24 | 842.11 | 102.29 | 89.48 | 1761.4 | 237.37 | 203.77 |
36 | 758.09 | 220.98 | 127.89 | 1925.0 | 716.16 | 406.96 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
He, S.; Lu, H.; Feng, Z.; Xiao, X. Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control. Actuators 2022, 11, 177. https://doi.org/10.3390/act11070177
He S, Lu H, Feng Z, Xiao X. Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control. Actuators. 2022; 11(7):177. https://doi.org/10.3390/act11070177
Chicago/Turabian StyleHe, Siyu, Haolin Lu, Zhao Feng, and Xiaohui Xiao. 2022. "Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control" Actuators 11, no. 7: 177. https://doi.org/10.3390/act11070177
APA StyleHe, S., Lu, H., Feng, Z., & Xiao, X. (2022). Position Tracking for Multi-Channel Double-Crystal Monochromator Scanning Based on Iterative Learning Control. Actuators, 11(7), 177. https://doi.org/10.3390/act11070177