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A delay‐dependent robust fuzzy MPC approach for nonlinear CSTR
Author(s) -
Chen QiuXia,
Yu Li
Publication year - 2010
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.20277
Subject(s) - continuous stirred tank reactor , control theory (sociology) , model predictive control , nonlinear system , fuzzy logic , linear matrix inequality , compensation (psychology) , mathematics , fuzzy control system , controller (irrigation) , mathematical optimization , computer science , control (management) , engineering , artificial intelligence , psychology , agronomy , quantum mechanics , chemical engineering , psychoanalysis , biology , physics
Based on Takagi–Sugeno (T–S) fuzzy models, a robust fuzzy model predictive control (MPC) algorithm is presented for a class of nonlinear time‐delay systems with input constraints. Delay‐dependent sufficient conditions for the robust stability of the closed‐loop system are derived, and the condition for the existence of the fuzzy model predictive controller is formulated in terms of nonlinear matrix inequality via the parallel distributed compensation (PDC) approach. By using a novel matrix transform technique, a receding optimization problem with linear matrix inequality (LMIs) constraints is constructed to design the desired controllers with an on‐line optimal receding horizon guaranteed cost. Finally, an example of continuous stirred tank reactors (CSTR) is given to demonstrate the effectiveness of the proposed results.