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Author: search.filters.author.Cappelletti, Carlos AlbertoSubject: search.filters.subject.linear parameter-varying

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    A Procedure for Determination of Reduced Polytopic Models Based on Robust Multi-Model Representation of Large Dimensions
    (Universidad Nacional de Misiones. Facultad de Ingeniería., 2023-11-03) Cappelletti, Carlos Alberto; Pipino, Hugo; Bernardi, Emanuel; Adam, Eduardo J.
    This study entails a meticulous examination of the dynamic characteristics exhibited by the continuous stirred tank reactor (CSTR) with the objective of establishing a robust multi-model representation that accurately captures the reactor behavior across its operational range. To achieve this, a methodology is presented, which incorporates parameter variations as uncertainties within the model. The result is a concise polytopic representation, reduced to its vertices, that effectively captures the system dynamics and encompasses the range of parameter uncertainties.
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    Adaptive Predictive Control for Industrial Processes
    (IEEE, 2021-11-05) Bernardi, Emanuel; Pipino, Hugo; Cappelletti, Carlos Alberto; Adam, Eduardo J.
    In this work a predictive controller formulation is developed within a linear parameter-varying formalism, which serves as a non-linear process model. The proposed strategy is an adaptive Model-based Predictive Controller (MPC), designed with terminal set constraints and considering the scheduling polytope of the model. At each sample time, two Quadratic Programming (QP) problems are solved: the first QP considers a backward horizon to find a virtual model-process tuning variable that defines the best LTI prediction model, considering the vertices of the polytopic system; then, the second QP uses this LTI model to optimise performances along a forward horizon. This paper ends with a realistic solar thermal collector process simulation, comparing the proposed MPC to other techniques from the literature. Discussions regarding the results, the design procedure and the computational effort are presented.