Data-based Robust MPC with Componentwise Hölder Kinky Inference

The authors have recently developed predictive controllers based on prediction models derived from experimental data, by means of a class of Hölder interpolation called kinky inference. This paper provides a step forward by proposing a novel estimation method based on componentwise Hölder interpolation. This allows to explicitly consider the contribution of each component on each output, yielding better estimations. Following the procedure used in previous works, this estimation method is used to provide a predictor for a nonlinear robust data-based predictive controller, whose performance and robustness is enhanced by the new setting. The properties of the proposed controller are demonstrated in a case study.