TY - JOUR
N2 - The paper is concerned with the presentation and analysis of the Dynamic Matrix Control (DMC) model predictive control algorithm with the representation of the process input trajectories by parametrised sums of Laguerre functions. First the formulation of the DMCL (DMC with Laguerre functions) algorithm is presented. The algorithm differs from the standard DMC one in the formulation of the decision variables of the optimization problem – coefficients of approximations by the Laguerre functions instead of control input values are these variables. Then the DMCL algorithm is applied to two multivariable benchmark problems to investigate properties of the algorithm and to provide a concise comparison with the standard DMC one. The problems with difficult dynamics are selected, which usually leads to longer prediction and control horizons. Benefits from using Laguerre functions were shown, especially evident for smaller sampling intervals.
L1 - http://sd.czasopisma.pan.pl/Content/121917/PDF/art03.pdf
L2 - http://sd.czasopisma.pan.pl/Content/121917
PY - 2021
IS - No 4
EP - 814
DO - 10.24425/acs.2021.139731
KW - process control
KW - model predictive control
KW - DMC algorithm
KW - Laguerre functions
A1 - Tatjewski, Piotr
PB - Committee of Automatic Control and Robotics PAS
VL - vol. 31
DA - 2021.12.27
T1 - Effectiveness of Dynamic Matrix Control algorithm with Laguerre functions
SP - 795
UR - http://sd.czasopisma.pan.pl/dlibra/publication/edition/121917
T2 - Archives of Control Sciences
ER -