2026/02/11 by Levi D. Reyes Premer, Arash J. Khabbazi, Kevin J. Kircher
#eess.SY #cs.SY #math.OC
We define trajectory predictive control (TPC) as a class of indirect data-driven predictive control (DDPC) methods that represent future outputs as linear in past inputs/outputs and future inputs. TPC unifies many DDPC variants with different predictor structures. We introduce a predictor with a state-space representation and show that with it, TPC inherits the mature theory of linear model predictive control. In numerical experiments, the state-space predictor outperforms existing predictors, especially for small training datasets.