Abstract
This paper presents the application of the multiagent paradigm to a distributed model-based predictive control (DMPC) scheme in order to improve its fault tolerance, give it the ability to dynamically adapt its strategy to optimize energy consumption, and to allow it to scale up. This approach is illustrated in the control of a canal simulated using realistic, physics-based 1D models in MatLab. The individual agent behavior, based on DMPC, and the multiagent composition mechanism are described. Presented simulation results illustrate the ability of the proposed control scheme to adapt to a hardware failure and to take global strategies into account.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Malaterre, P.O., Rogers, D.C., Schuurmans, J.: Classification of canal control algorithms. Journal of Irrigation and Drainage Engineering (1998)
Litrico, X., Fromion, V.: Modeling and Control of Hydrosystems - A Frequency Domain Approach. Springer-Verlag (2009)
Mayne, D.Q., Rawlings, J.B., Rao, C.V., Scokaert, P.O.M.: Constrained model predictive control: Stability and optimality. Automatica, 789–814 (2000)
Findeisen, R., Imsland, L., Allgöwer, F., Foss, B.A.: State and output feedback nonlinear model predictive control: An overview. Euro. J. of Control 9(3), 179–195 (2003)
Mayne, D.Q., Michalska, H.: Receding horizon control of nonlinear systems. IEEE Transactions on Automatic Control 35(7), 814–824 (1990)
Qin, S., Badgwell, T.: An overview of industrial model predictive control technology. In: Kantor, J., Garcia, C., Carnahan, B. (eds.) Fifth International Conference on Chemical Process Control - CPCV, pp. 232–256. American Institute of Chemical Engineers (1996)
Jamont, J.P., Occello, M., Lagréze, A.: A multiagent approach to manage communication in wireless instrumentation systems. Measurement 43(4), 489–503 (2010)
Matei, A.M.: Multi-agent system for monitoring and analysis prahova hydrographical basin. Technical report (2011)
Luo, J., Xu, L., Jamont, J.P., Zeng, L., Shi, Z.: Flood decision support system on agent grid: method and implementation. Enterprise Information Sys. 1(1), 49–68 (2007)
Rendón-Sallard, T., Sànchez-Marrè, M., Aulinas, M., Comas, J.: Designing a multi-agent system to simulate scenarios for decision-making in river basin systems. In: Proc. of the 9th Int. Conf. of the AI R&D, pp. 291–298. IOS Press (2006)
Nabais, J.L., Mendonça, L.F., Botto, M.A.: A multi-agent architecture for diagnosing simultaneous faults along water canals. In: Control Engineering Practice (2013)
van Oel, P.R., Krol, M.S., Hoekstra, A.Y., Taddei, R.R.: Feedback mechanisms between water availability and water use in a semi-arid river basin: A spatially explicit mas simulation approach. Environmental Modelling & Software 25(4), 433–443 (2010)
Occello, M., et al.: Designing organized agents for cooperation with real time constaints. In: Drogoul, A., Fukuda, T., Tambe, M. (eds.) CRW 1998. LNCS, vol. 1456, pp. 25–37. Springer, Heidelberg (1998)
Cohen, G., Zhu, D.L.: Decomposition coordination methods in large scale optimization problems: The nondifferentiable case and the use of augmented lagrangians. Advances in Large Scale Systems 1, 203–266 (1984)
Cohen, G.: Auxiliary problem principle and decomposition of optimization problems. Journal of Optimization Theory and Application 32(3) (1980)
Pham, V.T., Georges, D., Besançon, G.: Infinite-dimensional predictive control for hyperbolic systems. SIAM J. of Ctrl. and Optimisation (2012)
Scattolini, R.: Architectures for distributed and hierachical model predictive control. Journal for Process Control, 723–731 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Thang Pham, V., Raïevsky, C., Jamont, JP. (2014). A Multiagent Approach Using Model-Based Predictive Control for an Irrigation Canal. In: Bajo Perez, J., et al. Trends in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. Advances in Intelligent Systems and Computing, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-319-07476-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-07476-4_11
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07475-7
Online ISBN: 978-3-319-07476-4
eBook Packages: EngineeringEngineering (R0)