Multiple Steps Prediction with Nonlinear ARX Models
2004 (English)In: Proceedings of the 2004 IFAC Symposium on Nonlinear Control Systems, 2004Conference paper (Refereed)
Abstract NLARX (NonLinear AutoRegressive with eXogenous inputs) models are frequently used in black-box nonlinear system identication. Though it is easy to make one step ahead prediction with such models, multiple steps prediction is far from trivial. The main difficulty is that in general there is no easy way to compute the mathematical expectation of an output conditioned by past measurements. An optimal solution would require intensive numerical computations related to nonlinear filltering. The purpose of this paper is to investigate simple non optimal prediction methods. It is shown that cautions must be paid when using such methods, since their prediction behaviors may be radically different, depending on some detailed choice.
Place, publisher, year, edition, pages
Nonlinear system identification, NLARX model, Multiple steps prediction, Simulation
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-22554Local ID: 1819OAI: oai:DiVA.org:liu-22554DiVA: diva2:242867
2004 IFAC Symposium on Nonlinear Control Systems, Stuttgart, Germany, September, 2004