Article
Min-Max MPC based on a computationally efficient upper bound of the worst case cost
Author/s | Rodríguez Ramírez, Daniel
Alamo, Teodoro Camacho, Eduardo F. Muñoz de la Peña Sequedo, David |
Department | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Publication Date | 2006 |
Deposit Date | 2020-03-31 |
Published in |
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Abstract | Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their ... Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible case of a performance index have been used to reduce the computational burden. This paper proposes a computationally efficient MMMPC control strategy in which the worst case cost is approximated by an upper bound based on a diagonalization scheme. The upper bound can be computed with O(n3) operations and using only simple matrix operations. This implies that the algorithm can be coded easily even in non-mathematical oriented programming languages such as those found in industrial embedded control hardware. A simulation example is given in the paper. |
Citation | Rodríguez Ramírez, D., Alamo, T., Camacho, E.F. y Muñoz de la Peña Sequedo, D. (2006). Min-Max MPC based on a computationally efficient upper bound of the worst case cost. Journal of Process Control, 16 (5), 511-519. |
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