Robust model predictive controller with output feedback and target tracking

Autor(es)

Gonzalez, A. H. ^[1] ; Odloak, D. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Nacl Litoral, CONICET, Inst Technol Dev Chem Ind INTEC, Buenos Aires, DF - Argentina

^[2] Univ Sao Paulo, Dept Chem Engn, BR-05508 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IET Control Theory and Applications; v. 4, n. 8, p. 1377-1390, AUG 2010.
• Citações Web of Science: 9

Resumo

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system. (AU)

• Processo FAPESP: 06/57622-0 - Integracao da otimizacao em tempo real com o controlador mpc robusto.
• Beneficiário: Alejandro Hernan Gonzalez
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado