Abstract
This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system (CSTR). Moreover, the authors take into account a practical validation on an experimental communicating two tank system (CTTS).
Similar content being viewed by others
References
Bouzrara K, Mbarek A, Garna T, et al., Nonlinear predictive controller for uncertain process modeled by GOBF-Volterra models, International Journal of Modelling, Identification and Control, 2013, 19(4): 307–322.
Diouf C, Telescu M, Cloastre P, et al., On the use of equality constraints in the identification of volterra-laguerre models, IEEE Signal Processing Letters, 2012, 19(12): 857–860.
Ricardo J G B Campello, Gard Favier, andWagner C do Amaralc, Optimal expansions of discretetime Volterra models using Laguerre functions, Automatica, 2004, 40(5): 815–822.
Dumont G and Fu Y, Non-linear adaptive control via Laguerre expansion of Volterra kernels, Int. J. Adapt. Contr. Signal Process., 1993, 7(5): 367–382.
Boyd S and Chua L O, Fading memory and the problem of approximating nonlinear operators with Volterra series, IEEE Tr. Circuits and Systems, 1985, 32(11): 1150–1161.
Kibangou A Y, Favier G, and Hassani M M, Laguerre-Volterra filters optimization based on Laguerre spectra, EURASIP Journal on Advances in Signal Processing, 2005, 17: 2874–2887.
Garna T, Bouzrara K, Ragot J, et al., Nonlinear system modeling based on bilinear Laguerre orthonormal bases, ISA transactions, 2013, 52(3): 301–317.
Garna T, Bouzrara K, Ragot J, et al., Optimal expansions of discrete-time bilinear models using Laguerre functions, IMA Journal of Mathematical Control & Information, 2013, 31(3): 313–343.
Ghassen M, Abdelkader M, Tarek G, et al., Nonlinear model based predictive control using multiple models approach expanded on Laguerre bases, Wseas Transactions on Systems and Control, 2015, 10: 113–126.
Sbarbaro D and Johansen T A, Multiple local Laguerre models for modelling nonlinear dynamic systems of the Wiener class, IEE Proceedings, Control Theory Applications, 1997, 144(5): 375–380.
Sbarbaro D, Context sensitive networks for modelling nonlinear dynamic systems, Proceedings of 3rd European Control Conference, 1995, 3b: 2420–2425.
Boukhris A, Mourot G, and Ragot J, Non-linear dynamic system identification: A multi-model approach, International Journal of Control, 1999, 72(7–8): 591–604.
Orjuela R, Marx B, Ragot J, et al., State estimation for nonlinear systems using decoupled multiple model, International Journal of Modelling Identification and Control, 2008, 4(1): 59–67.
Bouzrara K, Garna T, Ragot J, et al., Decomposition of an ARX model on orthonormal Laguerre bases, ISA Transactions, 2012, 51(6): 848–860.
Demuth H, Beale M, and Hagan M, Neural Network Toolbox 5, User’s Guide, The MathWorks, 2007.
Filev D, Fuzzy modeling of complex systems, International Journal of Approximate Reasoning, 199, 5(3): 281–290.
Johansen T A and Foss A B, Constructing NARMAX using ARMAX models, International Journal of Control, 1993, 58(5): 1125–1153.
Johansen T A and Foss B A, Identification of non-linear system structure and parameters using regime decomposition, Automatica, 1995, 31(2): 321–326.
Narendra K S and Cheng X, Adaptive control of discrete-time systems using multiple models, IEEE Transactions on Automatic Control, 2000, 45(9): 1669–1686.
Bouzrara K, Garna T, Ragot J, et al., Online identification of the ARX model expansion on Laguerre orthonormal bases with filtres on model input and output, International Journal of Control, 2013, 86(3): 369–385.
Tanguy N, Morvan R, Vilbé P, et al., Online optimization of the time scale in adaptive Laguerrebased filters, IEEE Transactions on Signal Processing, 2000, 48(4): 1184–1187.
Seborg D E, Edger T F, and Millichamp D A, Process Dynamics and Control, John Wiley & Sons, 2004.
Author information
Authors and Affiliations
Corresponding author
Additional information
This paper was recommended for publication by Editor CHEN Jie.
Rights and permissions
About this article
Cite this article
Sameh, A., Abdelkader, M., Tarek, G. et al. Optimal Multimodel Representation by Laguerre Filters Applied to a Communicating Two Tank System. J Syst Sci Complex 31, 621–646 (2018). https://doi.org/10.1007/s11424-017-6047-2
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-017-6047-2