Conference paper
A novel tuning approach for offset-free MPC
Johannes Kepler University Linz1
Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Department of Chemical and Biochemical Engineering, Technical University of Denmark4
CAPEC-PROCESS, Department of Chemical and Biochemical Engineering, Technical University of Denmark5
CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark6
Since the beginnings in the chemical and process industry, model based predictive control strategies have become widely accepted. Often mentioned success factors for MPC are the use of optimization based on a plant model, the consideration of constraints, and an intuitive tuning. Indeed, if a nominal plant and overall objective are known, the tuning can become straightforward.
However, as soon as disturbances have to be taken into account, the tuning effort increases and becomes less intuitive. Against this background, a novel strategy to address the issues with unknown disturbances is proposed. The idea is to separate the nominal tuning process and extend the control by an outer loop, which ensures offset-free control.
The inner, nominal loop decouples the system and essentially leads to a first order response. This inner loop addresses the performance targets in the nominal case, and the outer loop provides offset-free control in case of unknown disturbances. The outer loop consists of feedback controllers adapting the reference, which due to the decoupling can be tuned by known guidelines.
The proposed strategy is presented and evaluated using a simulated case study.
Language: | English |
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Publisher: | IEEE |
Year: | 2015 |
Pages: | 545-550 |
Proceedings: | 14th European Control Conference (ECC 2015)European Control Conference |
ISBN: | 1467371602 , 3952426938 , 3952426946 , 9781467371605 , 9783952426937 and 9783952426944 |
Types: | Conference paper |
DOI: | 10.1109/ECC.2015.7330600 |
ORCIDs: | Jørgensen, John Bagterp and Huusom, Jakob Kjøbsted |
Kalman filters Linear programming Optimization Process control Standards Steady-state Tuning chemical industry control system synthesis feedback feedback controllers model based predictive control strategies nominal tuning process offset-free MPC offset-free control performance targets plant model predictive control process control process industry