Facultad Regional San Francisco

Permanent URI for this communityhttp://48.217.138.120/handle/20.500.12272/109

Browse

Author: search.filters.author.Cappelletti, Carlos AlbertoSubject: search.filters.subject.LMI

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Modeling of a Continuous Stirred Tank Reactor and Controller Design Using LMI Approaches
    (Wiley, 2025-01-07) Cappelletti, Carlos Alberto; Pipino, Hugo; Bernardi, Emanuel; Adam, Eduardo J.
    The design of non-linear control systems remains a challenge today, therefore through this work a procedure to obtain a vertex-reduced multi-model representation, without loss of convexity, is proposed as a suitable solution. That is, a novel approach which considers all parameter variations around the Continuous Stirred Tank Reactor (CSTR) system operating region is developed, resulting in a unique polytopic representation. After that, based on the linear matrix inequalities approach, a control scheme is developed to compute the optimal matrix gains, while the operating, states and inputs, constraints are satisfied and the stability conditions are ensured. Finally, the realistic simulation results highlight the model representation effectiveness in capturing the CSTR dynamic behavior in the operating region, despite parameter variations, allowing the optimal control law design, overcoming the non-linear system nature, to achieve the desired closed-loop system performance.
  • Thumbnail Image
    Item
    Optimum Multiobjective Regulator with Variable Gain Matrix Applied to an Industrial Process
    (2018-11-09) Cappelletti, Carlos Alberto; Bernardi, Emanuel; Pipino, Hugo; Adam, Eduardo J.
    In this paper, it is presented the design and tuning of a robust multi-objective regulator, with variable gain matrix through Linear Matrix Inequalities (LMI). The tuning presented here guarantees for an uncertain model under polytopic representation to satisfy simultaneously multiple objectives such as, asymptotic stability, minimization of the H2-norm, robustness and restrictions imposed on the manipulated variable. Finally, as an application example, this tuning is applied to a Continuous Stirred Tank Reactor (CSTR) typical of the chemical industry.