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Pole Placement-Based NMPC of Hammerstein Systems and Its Application to Grade Transition Control of Polypropylene
Author(s) -
Defeng He,
Li Yu
Publication year - 2011
Publication title -
journal of control science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 18
eISSN - 1687-5257
pISSN - 1687-5249
DOI - 10.1155/2012/630645
Subject(s) - control theory (sociology) , model predictive control , nonlinear system , controller (irrigation) , control (management) , stability (learning theory) , full state feedback , state (computer science) , control variable , optimal control , variable (mathematics) , state variable , computer science , engineering , mathematics , mathematical optimization , algorithm , physics , artificial intelligence , mathematical analysis , quantum mechanics , machine learning , agronomy , biology , thermodynamics
This paper presents a new nonlinear model predictive control (MPC) algorithm for Hammerstein systems subject to constraints on the state, input, and intermediate variable. Taking no account of constraints, a desired linear controller of the intermediate variable is obtained by applying pole placement to the linear subsystem. Then, actual control actions are determined in consideration of constraints by online solving a finite horizon optimal control problem, where only the first control is calculated and others are approximated to reduce the computational demand. Moreover, the asymptotic stability can be guaranteed in certain condition. Finally, the simulation example of the grade transition control of industrial polypropylene plants is used to demonstrate the effectiveness of the results proposed here

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