Estimación y Control Distribuidos de Sistemas sobre Redes de Comunicación

  1. Francisco R. Rubio 1
  2. Pablo Millán 2
  3. Luis Orihuela 2
  4. Carlos Vivas 1
  1. 1 Universidad de Sevilla
    info

    Universidad de Sevilla

    Sevilla, España

    ROR https://ror.org/03yxnpp24

  2. 2 Universidad Loyola
    info

    Universidad Loyola

    La Paz, Bolivia

    ROR https://ror.org/01wfnf418

Revista:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Año de publicación: 2014

Volumen: 11

Número: 4

Páginas: 377-388

Tipo: Artículo

DOI: 10.1016/J.RIAI.2014.08.001 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Revista iberoamericana de automática e informática industrial ( RIAI )

Resumen

Este trabajo presenta una técnica de diseño novedosa para la estimación y control distribuido de sistemas en red. Se considera un proceso discreto de gran escala controlado por una red de agentes que pueden recopilar información acerca de la evolución de la planta y aplicar las acciones de control para mejorar su comportamiento. El diseño propuesto es de especial interés cuando no se tiene observabilidad/controlabilidad local, de forma que es necesario utilizar la comunicación entre agentes para tener suficiente información dinámica del sistema. El objetivo global es diseñar un esquema de control y estimación distribuida, de forma que se obtengan estimaciones fiables por parte de los agentes así como un desempeño de control adecuado. El trabajo analiza dos esquemas diferentes de comunicación entre agentes, muestreo periódico y basado en eventos, proporcionando pruebas de estabilidad utilizando el criterio de Lyapunov y métodos de diseño en términos de desigualdades matriciales lineales LMIs (del inglés, Linear Matrix Inequalities). Se muestran resultados experimentales sobre un sistema de cuatro tanques para demostrar la eficacia de las metodologías propuestas.

Referencias bibliográficas

  • Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., Cayirci, E., 2002. Wireless sensor networks: a survey. Computer networks 38 (4), 393–422.
  • Alvarado, I., Limon, D., Muñoz de la Peña, D. and, J. M., Ridao, M. A., Scheu, H., Marquardt, W., Negenborn, R. R., De Schutter, B., Valencia, F., Espinosa, J., 2011. A comparative analysis of distributed MPC techniques applied to the HD-MPC four-tank benchmark. Journal of Process Control 21 (5), 800–815.
  • Anderson, B. D. O., Moore, J. B., 1981. Time-varying feedback laws for decentralized control. IEEE Transactions on Automatic Control 26 (5), 1133– 1139.
  • Antonelli, G., 2013. Interconnected dynamic systems: An overview on distributed control. IEEE Control Systems Magazine 33 (1), 76–88.
  • Briñón Arranz, L., Seuret, A., Canudas de Wit, C., December 2009. Translation ´ control of a fleet circular formation of AUVs under finite communication range. In: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference. Shangai, China, pp. 8345 – 8350.
  • Camponogara, E., Jia, D., Krogh, B. H., Talukdar, S., 2002. Distributed model predictive control. IEEE Control Systems 22 (1), 44–52.
  • Cortés, J., Martínez, S., Karatas, T., Bullo, F., 2004. Coverage control form mobile sensing networks. IEEE Transactions on Robotic and Automation 20 (2), 243–255.
  • D’Andrea, R., Dullerud, G. E., 2003. Distributed control design for spatially interconnected systems. IEEE Transactions on Automatic Control 48 (9), 1478–1495.
  • Davison, E. J., Chang, T. N., 1990. Decentralized stabilization and pole assignment for general proper systems. IEEE Transactions on Automatic Control 35 (6), 652–664.
  • Davison, E. J., Wang, S. H., 1973. On the stabilization of decentralized control systems. IEEE Transactions on Automatic Control 18 (5), 473–478.
  • Donkers, M., Heemels, W., 2012. Output-based event-triggered control with guaranteed l∞-gain and improved and decentralized event-triggering. IEEE Transactions on Automatic Control 57 (6), 1362–1376.
  • Dormido, S., Sánchez, J., Kofman, E., 2008. Muestreo, control y comunicación basado en eventos. Revista Iberoamericana de Automática e Informática Industrial 5 (1), 5–26.
  • Dunbar, W. B., 2007. Distributed receding horizon control of dynamically coupled nonlinear systems. IEEE Transactions on Automatic Control 52 (7), 1249–1263.
  • El Ghaoui, L., Oustry, F., AitRami, M., 1997. A cone complementary linearization algorithm for static output-feedback and related problems. IEEE Transactions on Automatic Control 42 (8), 1171–1176.
  • Estrin, D., Govindan, R., Heidemann, J., Kumar, S., August 1999. Next century challenges: scalable coordination in sensor networks. In: 5th ACM/IEEE International Conference on Mobile Computing and Networking. Seattle, WA, USA, pp. 263–270.
  • Guinaldo, M., Dimarogonas, D., Johansson, K., Sánchez, J., Dormido, S., 2013. Distributed event-based control strategies for interconnected linear systems. IET Control Theory and Applications 7 (6), 877–886.
  • Heemels, W., Donkers, M., Teel, A., 2013. Periodic event-triggered control for linear systems. IEEE Transactions on Automatic Control 58 (4), 847–861.
  • Heemels, W. P. M. H., Sandee, J. H., Van Den Bosch, P. P. J., 2008. Analysis of event-driven controllers for linear systems. International Journal of Control 81 (4), 571–590.
  • Iftar, A., August 1991. Decentralized optimal control with overlapping decompositions. In: IEEE International Conference on Systems Engineering. Dayton, Ohio, USA, pp. 299–302.
  • Iftar, A., 1993. Overlapping decentralized dynamic optimal control. International Journal of Control 58 (1), 187–209.
  • Instruments, F., 2012. Data Sheet: 33-041 Coupled Tank System for Matlab.
  • Johansson, K. H., 2000. The quadruple-tank process: a multivariable laboratory process with an adjustable zero. IEEE Transactions on Control Systems Technology 8 (3), 456–465.
  • Lee, J., Su, Y., Chung-Chou, S., 2007. A comparative study of wireless protocols: Bluetooth, UWB, Zigbee, and Wi-Fi, 46–51.
  • Lu, B., Oyekan, J., Gu, D., Hu, H., Nia, H. F. G., 2011. Mobile sensor networks for modelling environmental pollutant distribution. International Journal of Systems Science 42 (9), 1491–1505.
  • Lunze, J., Lehmann, D., 2010. A state-feedback approach to event-based control. Automatica 46, 211–215.
  • Lynch, J. P., Law, K. H., Blume, J. A., February 2002. Decentralized control techniques for large-scale civil structural systems. In: 20th International Modal Analysis Conference. Los Angeles, CA, USA, pp. 4–7.
  • Maestre, J. M., Negenborn, R., 2013. Distributed model predictive control made easy.
  • Millán, P., 2012. Robust analysis and design of networked control systems with applications. Ph.D. thesis, Universidad de Sevilla.
  • Millán, P., Orihuela, L., Vivas, C., Rubio, F., 2012. Control óptimo- L2 basado en red mediante funcionales de Lyapunov-Krasovskii. Revista Iberoamericana de Automática e Informática Industrial 9 (1), 14–23.
  • Negemborn, R. R., B., D. S., Hellendoorn, J., 2008. Multi-agent model predictive control for transportation networks: Serial versus parallel schemes. Engineering Applications of Artificial Intelligence 21 (3), 353–366.
  • Olfati-Saber, R., December 2005. Distributed Kalman filter with embedded consensus filters. In: 44th IEEE Conference on Decision and Control and the European Control Conference. Seville, Spain, pp. 8179–8184.
  • Orihuela, L., Millán, P., Vivas, C., Rubio, F. R., 2013. H2/H∞ control for discrete TDS with application to networked control systems: periodic and asynchronous communication. Optimal Control Applications and Methods, doi: 10.1002/oca.2101.
  • Roshany-Yamchi, S., Cychowski, M., Negenborn, R. R., De Schutter, B., Delaney, K., Connell, J., 2013. Kalman filter-based distributed predictive control of large-scale multi-rate systems: Application to power networks. IEEE Transactions on Control Systems Technology 21 (1), 27–39.
  • Salt, J., Casanova, V., Cuenca, A., Pizá, R., 2008. Sistemas de control basados en red. modelado y diseño de estructuras de control. Revista Iberoamericana de Automática e Informática Industrial 5 (3), 5–20.
  • Scattolini, R., 2009. Architectures for distributed and hierarchical Model Predictive Control-areview. Journal of Process Control 19 (5), 723–731.
  • Siljak, D. D., Zecevic, A. I., 2005. Control of large-scale systems: Beyond decentralized feedback. Annual Reviews in Control 29 (2), 169–179.
  • Tabuada, P., 2007. Event-triggered real-time scheduling of stabilizing. IEEE Transactions on Automatic Control 52 (9), 1680–1685.
  • Venkat, A. N., Rawlings, J. B., Wright, S. J., December 2005. Stability and optimality of distributed model predictive control. In: 44th IEEE Conference on Decision and Control and European Control Conference. Sevilla, Spain, pp. 6680–6685.
  • Xiao, L., Boyd, S., Lall, S., April 2005. A scheme for robust distributed sensor fusion based on average consensus. In: 4th International Symposium on Information Processing in Sensor Networks. Los Angeles,California,USA, pp. 4209–4214.
  • Yue, D., Han, Q. L., Lam, J., 2005. Network-based robust H∞ control of systems with uncertainty. Automatica 41 (6), 999–1007.
  • Yue, D., Tian, E., Han, Q. L., 2013. A delay system method for designing eventtriggered controllers of networked control systems. IEEE Transactions on Automatic Control 58 (2), 475–481.
Fuente de los datos: Dialnet