AN Improving NCS Stabilization Using a Predictive Pulsed Control Law
Keywords:
networked control systems, digital control, Bayesian predictionAbstract
The aim in this paper is experimentally to show that a predictive pulsed control law is able to enlarge the stabilizing sampling periods of a networked control system (NCS) more than the classical predictive ZOH-control law. Additionally, using a comparisson in the system response between the predictive pulsed control law and the predictive ZOH-control law, it is obtained that the pulsed control law requires less energy consumption to stabilize a NCS exposed to large time-delays. A 3-DOF Hover is used as case study.
References
[2] Briat, C. (2014). Spectral necessary and sufficient conditions for sampling-period-independent stabilisation of periodic and aperiodic sampled-data systems using a class of generalised sampleddata hold functions. International Journal of Control, 87(3), 612-621, 2014. https://doi.org/10.1080/00207179.2013.852249
[3] Castillo, O.; Benítez-Pérez, H. (2017). A novel technique to enlarge the maximum allowable delay bound in sampled-data systems. In Congreso Nacional de Control Automático 2017, Monterrey, Nuevo León, México. Asociación Mexicana de Control Automático, 2017.
[4] Castillo, O.; Benítez-Pérez, H.; Alvarez-Icaza, L. (2020). Novel analysis of sampled-data systems stabilised by a pulsed control signal. International Journal of Control, 0(0):1-9. https://doi.org/10.1080/00207179.2020.1735651
[5] Fridman, E. (2010). A refined input delay approach to sampled-data control. Automatica, 46(2):421-427. https://doi.org/10.1016/j.automatica.2009.11.017
[6] Fridman, E. (2014). Introduction to time-delay systems: Analysis and control. Springer. https://doi.org/10.1007/978-3-319-09393-2
[7] Halevi, Y.; Ray, A. (1988). Integrated communication and control systems: Part i-analysis. https://doi.org/10.1115/1.3152698
[8] Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering, 82(Series D):35-45. https://doi.org/10.1115/1.3662552
[9] Li, H.; Sun, Z.; Liu, H.; Chow, M.-Y. (2008). Predictive observer-based control for networked control systems with network-induced delay and packet dropout. Asian journal of control, 10(6):638- 650. https://doi.org/10.1002/asjc.65
[10] Li, X.-G.; Cela, A.; Niculescu, S.-I.; Reama, A. (2009a). A switched control method for networked control systems. IFAC Proceedings Volumes, 42(14):61-65. https://doi.org/10.3182/20090901-3-RO-4009.00007
[11] Li, X.-G.; Niculescu, S.-I.; Reama, A., et al. (2009b). Stability analysis of networked control systems based on a switched control. IFAC Proceedings Volumes, 42(20):358-363. https://doi.org/10.3182/20090924-3-IT-4005.00061
[12] Liu, B.; Xia, Y.; Mahmoud, M. S.; Wu, H.; Cui, S. (2012). New predictive control scheme for networked control systems. Circuits, Systems, and Signal Processing, 31(3):945-960. https://doi.org/10.1007/s00034-011-9359-9
[13] Naghshtabrizi, P.; Hespanha, J. P.; Teel, A. R. (2008). Exponential stability of impulsive systems with application to uncertain sampled-data systems. Systems & Control Letters, 57(5):378-385. https://doi.org/10.1016/j.sysconle.2007.10.009
[14] Naghshtabrizi, P.; Hespanha, J. P.; Teel, A. R. (2010). Stability of delay impulsive systems with application to networked control systems. Transactions of the Institute of Measurement and Control, 32(5):511-528. https://doi.org/10.1177/0142331208097841
[15] Seuret, A. (2012). A novel stability analysis of linear systems under asynchronous samplings. Automatica, 48(1):177-182. https://doi.org/10.1016/j.automatica.2011.09.033
[16] Su, J.; Li, B.; Chen, W.-H. (2015). On existence, optimality and asymptotic stability of the kalman filter with partially observed inputs. Automatica, 53, 149-154, 2015. https://doi.org/10.1016/j.automatica.2014.12.044
[17] Sun, X.-M.; Liu, G.-P.; Rees, D.; Wang, W. (2008). A novel method of stability analysis for networked control systems. IFAC Proceedings Volumes, 41(2), 4852-4856, 2008. https://doi.org/10.3182/20080706-5-KR-1001.00815
[18] Sí¤rkkí¤, S. (2013). Bayesian Filtering and Smoothing. Institute of Mathematical Statistics Textbooks. Cambridge University Press, 2013.
[19] Zheng, Y.; Fang, H.; Wang, Y. (2004). Kalman filter based fdi of networked control system. In Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No. 04EX788), IEEE, 2, 1330-1333, 2004. https://doi.org/10.1109/WCICA.2004.1340856
Additional Files
Published
Issue
Section
License
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
