Robust State Estimation of Nonlinear Systems Using High-Gain Transmissibility

Transmissibility operators are mathematical relations that connect unknown system outputs. In previous work, transmissibility operators showed robustness against unknown nonlinear system dynamics. Inspired by the high-gain observers, this paper extends transmissibility operators to the form of high-gain transmissibility. High-gain transmissibility is then used for the robust estimation of the system states. No direct measurements of the system states are available. The system model in this work can follow any non-canonical form. We show that the high-gain transmissibility estimator is able to robustly estimate the system states in the presence of unknown system nonlinearities that affect all states, and part of the output measurement is corrupted by noise. The potential of the proposed estimator is demonstrated through a simulation example.