Space-Filling Input Design for Nonlinear System Identification: A Reinforcement Learning Approach
Classical input design minimises the covariance of the estimated model parameters. For nonlinear black-box models, however, the dominant error is the bias induced by the model structure over the region of interest, which motivates space-filling strategies seeking to cover the system state space as uniformly as possible...
Charly Witmeur, Gonçalo G. Cruz, Maarten Schoukens et al.
· Zenodo (CERN European Organi... · 0 citations