Moving-horizon Guaranteed Parameter Estimation: Influence of the Measurement Error

We are concerned with moving-horizon guaranteed parameter estimation (MH-GPE) of non-linear systems in a context of bounded measurement error. The problem consists of approximating the set of all possible parameter values such that the predicted values of plant outputs match their corresponding measurements within prescribed error bounds. The principle of the moving-horizon estimation lies in selection of a subset of available measurements, which are then used for on-line calculations. Our objective is to study the influence of the measurement error on the estimation performance. We apply MH-GPE to a case study of a membrane process and find that the different types of error distribution and different error magnitudes have a significant effect on the estimation performance.