Abstract
Optical systems, such as a mobile LiDAR system, encounter mechanical disturbances associated with the condition of the road, resulting in significant misalignments in the optical paths within the system. To address this issue, considerable time is dedicated to the realignment process to restart the system. A suggested approach to overcome this challenge involves the implementation of automatic realignment through the control of the motion of the steering mirrors using an advanced control technique known as Model Predictive Control (MPC). This technique, which is relatively new in the field of optics, is widely utilized in the industry due to its capability to manage and resolve a broad range of problems that are inherent to industrial systems, particularly, those that are subject to constraints or undergo disturbances during operation. In this study, we utilize MPC on the optical chain, specifically the LiDAR component, to regulate the beam and promptly rectify any flexure that occurs during both constant and variable trajectories, as well as in the presence of disturbances. A comparative analysis is conducted with the PID controller to evaluate the performance of the advanced technique proposed.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
A. Pozzi and D. M. Raimondo, J. Energy Storage, 55, Part A, 105332 (2022); https://doi.org/10.1016/j.est.2022.105332
A. Ramdani, “Commande Prédictive des Systèmes Dynamiques Étude Comparative avec les Régulateurs Classiques,” Magister Dissertation, Dept. Auto. Elect. Indust. Pros., The M’Hamed Bougara University of Boumerdes, Boumerdes (2013).
J. ElHadj Ali, E. Feki, and A. Mami, Int. J. Adv. Comput. Sci. Appl., 10, 0100646 (2019); https://doi.org/10.14569/IJACSA.2019.0100646
A. Pawlowski, M. Schiavo, N. Latronico, et al., J. Process Control, 117, 98 (2022); https://doi.org/10.1016/j.jprocont.2022.07.007
S. Yuan, Z. Liu, L. Zheng, et al., Ocean Eng., 258, 111082 (2022); https://doi.org/10.1016/j.oceaneng.2022.111082
R. Chai, A. Tsourdos, H. Gao, et al., Automatica, 145, 110561 (2022); https://doi.org/10.1016/j.automatica.2022.110561
A. Ramdani and M. Traiche, Math. Sci. Eng. Aerosp., 13, 441 (2022).
Y. Zhu, W. Yan, and Y. Zhu, J. Process Control, 106, 122 (2021); https://doi.org/10.1016/J.JPROCONT.2021.08.018
M. Schulze and D. Gerrit, “On Closed-Loop Dynamics of ADMM-Based MPC,” arXiv: Optimization and Control, in: T. Faulwasser, M. A. Müller, and K. Worthmann (Eds.), Recent Advances in Model Predictive Control, Lecture Notes in Control and Information Sciences, Springer, Cham (2021), Vol. 485, pp. 107–134; https://doi.org/10.1007/978-3-030-63281-6 5
H. Li and C. L. E. Swartz, Comput. Ch. Eng., 122, 356 (2019); https://doi.org/10.1016/J.COMPCHEMENG.2018.08.028
K. Worthmann, M. W. Mehrez, G. K. I. Mann, et al., Automatica, 82, 243 (2017); https://doi.org/10.1016/J.AUTOMATICA.2017.04.038
N. M. Abbas, Int. J. Appl. Power Eng., 10, 244 (2021); https://doi.org/10.11591/IJAPE.V10.I3.PP244-252
Z. Lammouchi and K. Barra, Int. J. Appl. Power Eng., 4, 104 (2015); https://doi.org/10.11591/IJAPE.V4.I3.PP104-117
I. González-Torres, H. Miranda, C. Méndez-Barrios, et al., “Dynamic matrix predictive control on DC-AC modular multilevel converter: Design, control and realtime simulation,” in: 2017 IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, OH, USA (2017), pp. 4552-4559; https://doi.org/10.1109/ECCE.2017.8096780
W. Chang, W. Dong, L. Zhao, and Y. Qiang, “Model predictive control-based energy collaborative optimization management for energy storage system of virtual power plant,” in: 2020 19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), Xuzhou, China (2020), pp. 112-115; https://doi.org/10.1109/DCABES50732.2020.00037
Z. Ding, Z. Yang, C. Chen, et al., Mech. Syst. Signal Process., 167, Part A, 108543 (2022); https://doi.org/10.1016/J.YMSSP.2021.108543
L. Andong, J. Peng, Z. Wenan, et al., “Dynamic Matrix Control Method for Networked System Having Time Delay and Packet Loss,” Patent CN105353622A, Zhejiang University of Technology (2016).
Z. Wen-jie, Dynamic Matrix Control Algorithm Design and Simulation Based on MATLAB, Electronic Instrumentation Customers (2012).
Q. Hong, Y. Yuan, Z. Dongliang, et al., “Dynamic Matrix Control Method for Controlled Object with Integrals and Delay Link,” Shanghai University of Electric Power (2018).
G. Lu, Y. Lu, T. Deng, and H. Liu, “Automatic alignment of optical-beam-based GPS for free-space laser communication system,” in: Free-Space Laser Communication and Active Laser Illumination III (2004); Proc. SPIE, 5160; https://doi.org/10.1117/12.507410
E. Morrison, B. J. Meers, D. I. Robertson, and H. Ward, Appl. Opt., 33, 5041 (1994); https://doi.org/10.1364/AO.33.005041
Q. Fu, P. Tan, K. F. Liu, et al., Infrared Phys. Technol., 91, 187 (2018); https://doi.org/10.1016/j.infrared.2018.04.009
X. Liu, K. Liu, B. Qin, et al., Nucl. Instrum. Methods. Phys. Res. A, 837, 58 (2016); https://doi.org/10.1016/j.nima.2016.08.043
X. Liu, J. Guo, G. Li, et al., Results Phys., 12, 1044 (2019); https://doi.org/10.1016/j.rinp.2018.12.071
A. Sharma, V. Sivakumar, C. Bollig, et al., S. Afr. J. Sci., 105, 456 (2009); journals.co.za/doi/pdf/https://doi.org/10.10520/EJC96853
L. Shikwambana and V. Sivakumar, “Aerosol optical depth measurements over Pretoria using CSIR Lidar and sun-photometer: A case study,” in: 30th Annual Conference of South African Society For Atmospheric Sciences. Modeling and Observation of the Atmosphere, Proceedings of the Reviewed Papers, 01–02 Oct. 2014, pp. 138-141.
L. Shikwambana and V. Sivakumar, “Observation of clouds using the CSIR transportable LiDAR: A case study over Durban, South Africa,” Adv. Meteorol., 2016, 4184512 (2016); https://doi.org/10.1155/2016/4184512
P. Weibring, H. Edner, and S. Svanberg, Appl. Opt., 42, 3583 (2003); https://doi.org/10.1364/ao.42.003583
M. Tra¨ıche and A. Kedadra, “A Dual LiDAR System for Environmental Studies,” Society for Photo-Optical Instrumentation Engineers SPIE Newsroom 4801 (2013); https://doi.org/10.1117/2.1201306.004801
S. Sigurd, J. Process Control, 13, 291 (2003); https://doi.org/10.1016/S0959-1524(02)00062-8
C. R. Cutler and P. S. Ramaker, “Dynamic matrix control — A computer algorithm,” in: Proceedings of the Joint Automatic Control Conference, San Francisco, CA, USA (1980); paper No. WP5-B; https://doi.org/10.1109/JACC.1980.4232009
S. J. Qin and T. A. Badgwell, Control Eng. Pract., 11, 733 (2003); https://doi.org/10.1016/S0967-0661(02)00186-7
P. Tatjewski, Advanced Control of Industrial Processes: Structures and Algorithms, Springer Science & Business Media, London (2007).
A. Ramdani, S. Grouni, and K. Bouallegue, Advanced Trajectory Tracking Control Applied to Dynamic System with Disturbance, International Publisher & C.O (IPCO) (2014). pp.120-128.
E. Seborg, T. F. Edgar, D. A. Mellichamp, and F. J. Doyle, Process Dynamics and Control, International Student Version, Wiley (2011), 3rd ed.
E. F. Camacho and C. Bordons, “Model predictive controllers,” in: Model Predictive control. Advanced Textbooks in Control and Signal Processing, Springer, London (2007); https://doi.org/10.1007/978-0-85729-398-5 2
A. Ramdani, Elaboration des Techniques de Commandes Prédictives: Application à une Chaine Optique, Ph.D. Theses, Dept. Auto. Elect. Indust. Proc., The M’Hamed Bougara Univ. of Boumerdes., Boumerdes (2018).
C. A. Smith and A. B. Corripio, Principles and Practice of Automatic Process Control, Wiley (1997), 2nd ed.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ramdani, A., Traïche, M. & Grouni, S. Handling Disturbance in Optical Beam Alignment Using the MPC Approach. J Russ Laser Res 45, 189–201 (2024). https://doi.org/10.1007/s10946-024-10203-8
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10946-024-10203-8