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Identification of parametric models : from experimental data
Eric Walter,Luc Pronzato +1 more
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The article was published on 1997-01-01 and is currently open access. It has received 1251 citations till now. The article focuses on the topics: Parametric model & Experimental data.read more
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Non-linear robust identification using evolutionary algorithms
TL;DR: The methodology proposes that the RI problem is transformed into a multimodal optimization problem with an infinite number of global minima which constitute the FPS, and a special genetic algorithm (@e-GA), inspired by Multiobjective Evolutionary Algorithms, is presented.
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Application of spectral deconvolution and inverse mechanistic modelling as a tool for root cause investigation in protein chromatography
TL;DR: The established tool for root cause investigation is a valuable approach to rapidly identify process variations, aging of columns, or processing errors in protein chromatography and might help to minimize batch rejections or contribute to an increased productivity.
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Formal Solution to Systems of Interval Linear or Non-Linear Equations
TL;DR: It is shown that the modal intervals are a suitable tool to approach problems where logical reference appear and it is possible to give a logical meaning to general solutions of the system of equations obtained by means of an algorithm whose convergence conditions are studied.
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Structural identifiability analysis of a cardiovascular system model.
Antoine Pironet,Pierre Dauby,J. Geoffrey Chase,Paul D. Docherty,James A. Revie,Thomas Desaive +5 more
TL;DR: By manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable and may be considered suitable for use in diagnosis.
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Recent advances in bias and froth depth control in flotation columns
TL;DR: In this paper, the authors present a review of recent work done at Universite Laval in the field of column flotation instrumentation and control, focusing on the way the available information, from sensors and quantitative or even qualitative relationships, may be used to reach the control objectives.