Robust unknown Input observer design for uncertain and noisy OSL-QIB nonlinear systems

Abstract

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In this paper, the problem of designing a robust unknown input observer (RUIO) for quadratically inner bounded (QIB), one-sided Lipschitz (OSL) nonlinear systems in the presence of noise and unknown inputs is addressed. This RUIO is formulated as a convex optimization problem where parameter uncertainty and noise are considered. Sufficient conditions for observer gain synthesis are shown to be equivalent to solving a finite set of Linear Matrix Inequalities (LMIs) and a Linear Matrix Equality (LME). Two illustrative examples, a bioreactor for biomass production from substrate consumption and a robot manipulator, are used to test the effectiveness of the approach in the presence of unknown inputs, parameter uncertainty, and measurement noise.

This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the projects SaCoAV (ref. PID2020-114244RB-I00) and L-BEST (PID2020- 115905RB-C21).

Peer Reviewed

Postprint (author's final draft)