Adaptive identification of continuous-time MIMO state-space models

This paper studies the problem of identifying linear continuous-time state-space models from input-output measurements. An adaptive identifier is developed for the online estimation of both the state and the model parameters in a deterministic framework. Our approach is a non parametric one in the sense that it provides an arbitrary realization of the system. It relies on ideas from the subspace identification literature and adaptive observer.