Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Multi-objective performance optimisation for model predictive control by goal attainment
AU - Exadaktylos, Vasileios
AU - Taylor, C. James
PY - 2010
Y1 - 2010
N2 - This paper proposes an approach for performance tuning of Model Predictive Control (MPC) using goal-attainment optimisation of the cost function weighting matrices. The approach is developed for three formulations of the control problem: (i) minimal and (ii) non-minimal design based on the same cost function; and (iii) a non-minimal MPC approach with an explicit integral-of-error state variable and modified cost function. This approach is based on earlier research into multi-objective optimisation for Proportional-Integral-Plus (PIP) control systems. Simulation experiments for a 3-input, 3-output Shell Heavy Oil Fractionator model illustrate the feasibility of MPC goal-attainment for multivariable decoupling and attainment of a specific output response. For this example, the integral-of-error state variable offers improved design flexibility and hence, when it is combined with the proposed tuning method, yields an improved closed loop response in comparison to minimal MPC.
AB - This paper proposes an approach for performance tuning of Model Predictive Control (MPC) using goal-attainment optimisation of the cost function weighting matrices. The approach is developed for three formulations of the control problem: (i) minimal and (ii) non-minimal design based on the same cost function; and (iii) a non-minimal MPC approach with an explicit integral-of-error state variable and modified cost function. This approach is based on earlier research into multi-objective optimisation for Proportional-Integral-Plus (PIP) control systems. Simulation experiments for a 3-input, 3-output Shell Heavy Oil Fractionator model illustrate the feasibility of MPC goal-attainment for multivariable decoupling and attainment of a specific output response. For this example, the integral-of-error state variable offers improved design flexibility and hence, when it is combined with the proposed tuning method, yields an improved closed loop response in comparison to minimal MPC.
KW - Model Predictive Control
KW - Non-Minimal State Space
KW - Optimal Controller Tuning
KW - Decoupling
U2 - 10.1080/00207171003736295
DO - 10.1080/00207171003736295
M3 - Journal article
VL - 83
SP - 1374
EP - 1386
JO - International Journal of Control
JF - International Journal of Control
SN - 0020-7179
IS - 7
ER -