Linear vs. Nonlinear MPC: A Case Study

SILVINA INES BIAGIOLA; ANIA LUSSON CERVANTEZ; OSVALDO ENRIQUE AGAMENNONI; JOSE LUIS FIGUEROA

San Nicolas

Workshop; X Reunión de trabajo en Procesamiento de la Información y Control; 2003

Universidad Tecnologica Nacional

Model predictive control has become very popular due to its effectiveness in dealing with nonlinear, multivariable and/or hard-constrained plants. Although linear MPC can be applied for controlling nonlinear processes by obtaining a linearized model of the plant, this is only valid in a limited region. Therefore, a substantial improvement can be achieved by using the whole knowledge of the process dynamics, specially in the presence of marked nonlinearities. In this work three MPC schemes are compared to attain a better understanding of the effects of modeling simplifications or linearization typically performed in standard implementations. As an illustrative case, a pH neutralization process is dealt with.