Event-Triggered Data Selection for Online Frequency-Domain Identification
The paper introduces an event-triggered data selection method for remote frequency-domain identification of systems with changing dynamics. Instead of sending all measurements, a local unit only transmits data when it is relevant. Relevance is determined by combining information about estimation uncertainty and evidence of model mismatch, successfully reducing communication while maintaining high accuracy and fast adaptation to system changes.