Place: TEAMS meeting
NONLINEAR MODEL ESTIMATION VIA LINEARIZATION AROUND LARGE SIGNALS by Mehrad Ghasem Sharabiany
Abstract: In this seminar, a method for identifying a class of nonlinear systems from input-output data based on the linearization of the system around a varying working point will be presented. For this purpose, the system will be excited twice with an arbitrary input signal, called large signal, and with the same signal plus a small perturbation. It will be shown that in this manner, the system can be approximated as an LPV model around the large signals. Then, it will be shown that a nonlinear approximation can be derived from this LPV model with a technique presented in this work. This nonlinear model somehow reveals the structure of the nonlinear system with an initial estimate of its parameters. Finally, this nonlinear model will be used as a starting point for nonlinear system identification from noisy input-noisy output data along the same trajectory.