DocumentCode :
2902985
Title :
A tuning procedure for ARX-based MPC of multivariate processes
Author :
Olesen, Daniel Haugaard ; Huusom, Jakob Kjobsted ; Jorgensen, John Bagterp
Author_Institution :
DTU Compute, Tech. Univ. of Denmark, Lyngby, Denmark
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
1721
Lastpage :
1726
Abstract :
We present an optimization based tuning procedure with certain robustness properties for an offset free Model Predictive Controller (MPC). The MPC is designed for multivariate processes that can be represented by an ARX model. The stochastic model of the ARX model identified from input-output data is modified with an ARMA model designed as part of the MPC-design procedure to ensure offset-free control. The MPC is designed and implemented based on a state space model in innovation form. Expressions for the closed-loop dynamics of the unconstrained system is used to derive the sensitivity function of this system. The closed-loop expressions are also used to numerically evaluate absolute integral performance measures. Due to the closed-loop expressions these evaluations can be done relative quickly. Consequently, the tuning may be performed by numerical minimization of the integrated absolute error subject to a constraint on the maximum of the sensitivity function. The latter constraint provides a robustness measure that is essential for the procedure. The method is demonstrated for two simulated examples: A Wood-Berry distillation column example and a cement mill example.
Keywords :
closed loop systems; control system synthesis; multivariable control systems; optimisation; predictive control; robust control; state-space methods; ARMA model; ARX model; ARX-based MPC; MPC-design procedure; Wood-Berry distillation column example; absolute integral performance measures; cement mill example; closed-loop dynamics; integrated absolute error; multivariate processes; numerical minimization; offset free model predictive controller; optimization based tuning procedure; robustness properties; state space model; Aerospace electronics; Closed loop systems; Noise; Noise measurement; Robustness; Sensitivity; Tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580084
Filename :
6580084
Link To Document :
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