Partial least squares(PLS) regression has been widely used to capture the relationship between inputs and outputs in static system modeling. Several dynamic PLS algorithms were proposed to capture the characteristic of dynamic systems. However, none of these algorithms provides an explicit description for dynamic inner model and outer model. In this paper, a dynamic inner PLS is proposed for dynamic system modelling. The proposed algorithm gives explicit dynamic inner model and makes inner model and outer model consistent at the same time. Several examples are given to show the effectiveness of the proposed algorithm.
|Number of pages||6|
|Early online date||25 Sept 2015|
|Publication status||Published - 2015|
|Event||9th IFAC Symposium on Advanced Control of Chemical Processes, ADCHEM 2015 - , Canada|
Duration: 7 Jun 2015 → 10 Jun 2015
- Data-driven modeling
- Dynamic partial least squares