Design of a robust nonlinear receding-horizon observer - First-order and second-order approximations

Abstract

The objective of this study is to design a robust receding-horizon observer for systems described by nonlinear models with uncertain parameters. Robustification in the presence of model uncertainties naturally leads to the formulation of a nonlinear min-max optimization problem, which can be converted to a simpler minimization problem using approximation along a nominal trajectory. In this study, the suitability of first-order and second-order approximations is investigated. These methods are evaluated in simulation and with experimental data from continuous cultures of phytoplankton. © 2009 Springer Berlin Heidelberg.