Integration of real-time optimization and model predictive control

This paper proposes a controller design approach that integrates RTO and MPC for the control of constrained uncertain nonlinear systems. Assuming that the economic function is a known function of constrained system’s states, parameterized by unknown parameters and time-varying, the controller design...

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Vydáno v:Journal of process control Ročník 20; číslo 2; s. 125 - 133
Hlavní autoři: Adetola, V., Guay, M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.02.2010
Témata:
Adaptive control
Model predictive control
Real-time optimization
Real-time optimization
Model predictive control
Adaptive control
ISSN:0959-1524, 1873-2771
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Shrnutí:This paper proposes a controller design approach that integrates RTO and MPC for the control of constrained uncertain nonlinear systems. Assuming that the economic function is a known function of constrained system’s states, parameterized by unknown parameters and time-varying, the controller design objective is to simultaneously identify and regulate the system to the optimal operating point. The approach relies on a novel set-based parameter estimation routine and a robust model predictive controller that takes into the effect of parameter estimation errors. A simulation example is used to demonstrate the effectiveness of the design technique.
ISSN:0959-1524
1873-2771
DOI:10.1016/j.jprocont.2009.09.001