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.
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Goffaux, G., Wouwer, A.V. (2009). Design of a Robust Nonlinear Receding-Horizon Observer - First-Order and Second-Order Approximations. In: Magni, L., Raimondo, D.M., Allgöwer, F. (eds) Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01094-1_24
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DOI: https://doi.org/10.1007/978-3-642-01094-1_24
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