On the development and application of a continuous-discrete recursive prediction error algorithm.
Recursive state and parameter reconstruction is a well-established field in control theory. In the current paper we derive a continuous-discrete version of recursive prediction error algorithm and apply the filter in an environmental and biological setting as a possible alternative to the well-known extended Kalman filter. The framework from which the derivation is started is the so-called 'innovations-format' of the (continuous time) system model, including (discrete time) measurements. After the algorithm has been motivated and derived, it is subsequently applied to hypothetical and 'real-life' case studies including reconstruction of biokinetic parameters and parameters characterizing the dynamics of a river in the United Kingdom. Advantages and characteristics of the method are discussed.
Stigter
J D
JD
Systems and Control Group, Wageningen University and Research Center, Bornsesteeg 59, Wageningen 6708 PD, The Netherlands. hans.stigter@wur.nl
Beck
M B
MB
D000465:Algorithms; D018533:Biomass; D019149:Bioreactors; D003198:Computer Simulation; D017753:Ecosystem; D005374:Filtration; D008962:Models, Theoretical; D012235:Rhodamines; D045483:Rivers
D012235:Rhodamines; C222011:rhodamine WT