Abstract
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom layer computes the weighting matrices of the cost function from a desired closed-loop bandwidth while the top layer aims at finding the optimal bandwidth. This optimum corresponds to the optimal balance between the robustness and nominal performance of the closed-loop system. To find the optimal bandwidth, the extremum seeking (ES) algorithm, a form of non-model-based adaptive optimisation, is proposed. The auto-tuning approach is tested on a binary distillation column model. It is shown that the auto-tuning approach enables the MPC system to track its optimal closed-loop bandwidth and therefore obtain the minimum output variance.
| Original language | English |
|---|---|
| Pages (from-to) | 2189-2194 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 47 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | 19th IFAC World Congress on International Federation of Automatic Control ( IFAC 2014) - Cape Town International Convention Centre, Cape Town, South Africa Duration: 24 Aug 2014 → 29 Aug 2014 Conference number: 19 http://www.ifac2014.org |
Keywords
- Auto-tuning
- Closed-loop bandwidth
- Extremum seeking
- Model predictive control
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Cite this
Tran, N., Scholten, J., Ozkan, L., & Backx, A. C. P. M. (2014). A model-free approach for auto-tuning of model predictive control. IFAC-PapersOnLine, 47(3), 2189-2194. https://doi.org/10.3182/20140824-6-ZA-1003.01494