A new Bayesian computational approach is developed to estimate spatially varying parameters. The sparse grid collocation method is adopted to parameterize the spatial field. Based on a hierarchically structured sparse grid, a multiscale representation of the spatial field is constructed. An adaptive refinement strategy is then used for computing the spatially varying parameter. A sequential Mon...

Based on the extension of behavioral theory and Fundamental Lemma for Linear Parameter-Varying (LPV) systems, this paper introduces a Data-driven Predictive Control (DPC) scheme capable to ensure reference tracking satisfaction Input-Output (IO) constraints an unknown system under conditions that (i) can be represented in LPV form (ii) informative data-set containing measured IO scheduling traj...

Time-varying parameter (TVP) models often assume that the TVPs evolve according to a random walk. This assumption, however, might be questionable since it implies coefficients change smoothly and in an unbounded manner. assumption is relaxed by proposing flexible law of motion for large-scale vector autoregressions (VARs). Instead imposing restrictive walk evolution latent states, hierarchical ...

EDITORIAL article Front. Control Eng., 18 August 2022Sec. and Automation Systems Volume 3 - 2022 | https://doi.org/10.3389/fcteg.2022.970136