Identification of nonlinear systems with nonlinear parameterization

A contraction based identification scheme for systems with nonlinear parameterizations is developed in this paper. Given a system with a general parameterization, an identification model is proposed such that time evolution of estimation error is composed by two blocks of parameterization: one linear and one nonlinear function of linear parameterization. A particular identification algorithm, based on the proportional-integral adaptive scheme, is then formulated. Exponential convergence among the underlined and desired identification systems trajectories is analyzed by means of an averaged version for contraction.