Control Systems and Identification
This cluster of papers covers advances in system identification techniques, including parameter estimation for nonlinear models, data-driven control, model-based control, feedback controllers, state estimation for multivariable systems, and the development of recursive algorithms. The papers also discuss model selection approaches and optimal experiment design for system identification.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.