Abstract
This paper deals with modeling and identification of a real irrigation system (Bourne-FRANCE) on the basis of real time-series. Black box and knowledge based modeling with various identification methods, iterative and non-iterative, are tested on real data.
Between these methods, the recursive Kalman filter ensures the tracking of the systems parameters (time varying system with time delay), and the subspace methods (non iterative) are always convergent and numerically stable and also, the system order do not have to be known in advance.