Models and methods for hybrid system identification: A systematic survey

Reference:
A. Moradvandi, R.E.F. Lindeboom, E. Abraham, and B. De Schutter, "Models and methods for hybrid system identification: A systematic survey," Proceedings of the 22nd IFAC World Congress, Yokohama, Japan, pp. 95-107, July 2023.

Abstract:
Dynamical systems and processes that either exhibit non-smooth behaviors (e.g. through logic control or natural phenomena) or work in different modes of operation are usually represented using hybrid systems models, i.e. mathematical models that combine continuous dynamics with discrete-event dynamics. Identification of a hybrid system includes finding switching patterns and identification of model parameters to obtain a data-driven model. This survey paper provides a systematic review of models (how to parameterize the system) and methods (how to identify unknown parameters) proposed for hybrid system identification with an exposition of recent advances and developments, and further research directions.