AI RESEARCH
Learning Surrogate LPV State-Space Models with Uncertainty Quantification
arXiv CS.LG
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ArXi:2603.29532v1 Announce Type: cross The Linear Parameter-Varying (LPV) framework enables the construction of surrogate models of complex nonlinear and high-dimensional systems, facilitating efficient stability and performance analysis together with controller design. Despite significant advances in data-driven LPV modelling, existing approaches do not quantify the uncertainty of the obtained LPV models. Consequently, assessing model reliability for analysis and control or detecting operation outside the.