A New Strategy of Validities’ Computation for Multimodel Approach: Experimental Validation

The evaluation of validities is a fundamental step in the design of the multimodel approach. Indeed, it is thanks to validities that we estimate the contribution of each base-model in the reproduction of the behavior of the global process in a given operating area. These coefficients are calculated most commonly by the approach of the residues formulated by the distance between the real output and the sub-models’ outputs. In this paper, a strategy allowing to improve the performances of the residues’ approach in terms of precision and robustness is proposed. This strategy is based on a quasi-hierarchical structuring. A simulation example and a validation on a semi-batch reactor showed the interest and the effectiveness of the proposed strategy.

[1]  Mekki Ksouri,et al.  Multimodel Approach using Neural Networks for Complex Systems Modeling and Identification , 2008 .

[2]  Roderick Murray-Smith,et al.  Multiple Model Approaches to Modelling and Control , 1997 .

[3]  Dhaou Soudani,et al.  On the Internal Multi-Model Control of Uncertain Discrete-Time Systems , 2016 .

[4]  B. Marx,et al.  Nonlinear system identification using heterogeneous multiple models , 2013, Int. J. Appl. Math. Comput. Sci..

[5]  Hajer Bouzaouache Output Feedback Controller Synthesis for Discrete-Time Nonlinear Systems , 2017 .

[6]  Mohamed Benrejeb,et al.  Multimodel control design using unsupervised classifiers , 2012 .

[7]  José Ragot,et al.  Systematic Multimodeling Methodology Applied to an Activated Sludge Reactor Model , 2010 .

[8]  Mohamed Benrejeb,et al.  Multi-model approach to characterize human handwriting motion , 2015, Biological Cybernetics.

[9]  François Delmotte Analyse multi-modèle , 1997 .

[10]  Didier Maquin,et al.  State estimation of nonlinear systems based on heterogeneous multiple models: Some recent theoretical results , 2009 .

[11]  M. Ksouri-Lahmari,et al.  Contributions à la commande multimodèle des processus complexes , 1999 .

[12]  Ridha Ben Abdennour,et al.  Optimal Systematic Determination of Models’ Base for Multimodel Representation: Real Time Application , 2014, Int. J. Autom. Comput..

[13]  Moufida Ksouri,et al.  Diagnosis by the multimodel approach in the frequency domain , 2011, 2011 4th International Conference on Logistics.

[14]  Pierre Borne,et al.  A Neural Approach of Multimodel Representation of Complex Processes , 2008, Int. J. Comput. Commun. Control.

[15]  Tor Arne Johansen,et al.  Nonlinear Local Model Representation For Adaptive Systems , 1992, Singapore International Conference on Intelligent Control and Instrumentation [Proceedings 1992].

[16]  Faouzi M'Sahli,et al.  A multimodel approach for a nonlinear system based on neural network validity , 2011, Int. J. Intell. Comput. Cybern..

[17]  Ameur Sassi,et al.  New Stability Conditions for Nonlinear Systems Described by Multiple Model Approach , 2016 .

[18]  Kamel Abderrahim,et al.  New Method for the Systematic Determination of the Model's Base of Time Varying Delay System , 2012 .