### Uittreksel

Taal | Engels |
---|---|

Titel | Proceedings of the 2014 American Control Conference |

Uitgeverij | Institute of Electrical and Electronics Engineers |

Pagina's | 4889-4894 |

ISBN van geprinte versie | 978-1-4799-3274-0 |

DOI's | |

Status | Gepubliceerd - jun 2014 |

Evenement | 2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA - Hilton Portland & Executive Tower , Portland, OR, Verenigde Staten van Amerika Duur: 4 jun 2014 → 6 jun 2014 http://acc2014.a2c2.org/ |

### Congres

Congres | 2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA |
---|---|

Verkorte titel | ACC 2014 |

Land | Verenigde Staten van Amerika |

Stad | Portland, OR |

Periode | 4/06/14 → 6/06/14 |

Ander | 2014 American Control Conference, Portland, OR |

Internet adres |

### Vingerafdruk

### Citeer dit

*Proceedings of the 2014 American Control Conference*(blz. 4889-4894). Institute of Electrical and Electronics Engineers. DOI: 10.1109/ACC.2014.6858951

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*Proceedings of the 2014 American Control Conference.*Institute of Electrical and Electronics Engineers, blz. 4889-4894, Portland, OR, Verenigde Staten van Amerika, 4/06/14. DOI: 10.1109/ACC.2014.6858951

**Generalized predictive control tuning by controller matching.** / Tran, N.; Ryvo Octaviano, R.; Ozkan, L.; Backx, T.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Generalized predictive control tuning by controller matching

AU - Tran,N.

AU - Ryvo Octaviano,R.

AU - Ozkan,L.

AU - Backx,T.

PY - 2014/6

Y1 - 2014/6

N2 - The tuning of state-space model predictive control (MPC) based on reverse engineering has been investigated in literature using the inverse optimality problem ( [1] and [2]). The aim of the inverse optimality is to find the tuning parameters of MPC to obtain the same behavior as an arbitrary linear-time-invariant (LTI) controller (favorite controller). This requires equal control horizon and prediction horizon, and loop-shifting is often used to handle non-strictly-proper favorite controllers. This paper presents a reverse-engineering tuning method for MPC based on transfer function formulation, also known as generalized predictive control (GPC). The feasibility conditions of the matching of a GPC with a favorite controller are investigated. This approach uses a control horizon equal to one and does not require any loop-shifting techniques to deal with non-strictly-proper favorite controllers. The method is applied to a binary distillation column example

AB - The tuning of state-space model predictive control (MPC) based on reverse engineering has been investigated in literature using the inverse optimality problem ( [1] and [2]). The aim of the inverse optimality is to find the tuning parameters of MPC to obtain the same behavior as an arbitrary linear-time-invariant (LTI) controller (favorite controller). This requires equal control horizon and prediction horizon, and loop-shifting is often used to handle non-strictly-proper favorite controllers. This paper presents a reverse-engineering tuning method for MPC based on transfer function formulation, also known as generalized predictive control (GPC). The feasibility conditions of the matching of a GPC with a favorite controller are investigated. This approach uses a control horizon equal to one and does not require any loop-shifting techniques to deal with non-strictly-proper favorite controllers. The method is applied to a binary distillation column example

U2 - 10.1109/ACC.2014.6858951

DO - 10.1109/ACC.2014.6858951

M3 - Conference contribution

SN - 978-1-4799-3274-0

SP - 4889

EP - 4894

BT - Proceedings of the 2014 American Control Conference

PB - Institute of Electrical and Electronics Engineers

ER -