ROBUST FEEDBACK LINEARIZATION WITHOUT FULL STATE INFORMATION

Robust feedback linearization of nonlinear systems without full state information is studied in this paper. The state is reconstructed from the output and the input by a linear observer combined with a diffeomorphism. It is shown that a separation principle holds, i.e., the estimated state can be used for performing robust feedback linearization, which exactly transforms the nonlinear system into a linear system equal to its linear approximation around a nominal operating point. Local stability of the resulting closed loop is proved by theoretical arguments and its robustness is illustrated through an example.