Online continuous time system identification in the presence of impulsive terms

Abstract

Online parameters estimation algorithms are proposed for continuous time systems subject to structured perturbations. Using a distribution framework, a matrix pencil structure, whose polynomial order is characterized by the nature of the singularities describing the impulsive effects, is proposed for the modeling of perturbed systems with different disturbance types. Then, using an appropriate projection subspace, the rectangular pencils are reformulated as square generalized eigenvalue problems subject to linear constraints, from which unperturbed regression are derived. This approach allows for the implementation of recursive estimation schemes, free of penalty terms. An identifiability analysis is also conducted, and theoretical results are illustrated with experimental and simulated data.

Hierarchical estimation methods based on the penalty term for controlled autoregressive systems with colored noises

“…[40][41][42][43] The recursive methods are also suitable for on-line identification, which update the parameter estimates in real time while collecting data. 44 The traditional online recursive identification approaches are based on the least squares principle. Lv et al proposed a two-step identification algorithm based on the recursive least squares principle to solve the parameter identification problem of linear discrete period time-varying systems.…”

“…So far, the recursive identification methods have always been active in the field of system identification 40–43 . The recursive methods are also suitable for on‐line identification, which update the parameter estimates in real time while collecting data 44 . The traditional online recursive identification approaches are based on the least squares principle.…”