Simultaneous ML estimation of state and parameters for hyperbolic systems with noisy boundary condition

Bagchi, A. and Brummelhuis ten, P.G.J. (1990) Simultaneous ML estimation of state and parameters for hyperbolic systems with noisy boundary condition. In: 29th IEEE Conference on Decision and Control, 1990, Honolulu, Hawaii.

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Abstract:	A method to estimate simultaneously states and parameters of a discrete-time hyperbolic system with noisy boundary conditions is presented. This method is based on maximization of a likelihood (ML) function. The ML function leads to a two-point boundary value problem of considerable complexity. Restricted discrete-time problems, the large dimension of the state vector and the direct solution of the two-point boundary value problem may lead to a huge computational load. An alternative computational method is proposed which is much faster and makes use of specific features of the hyperbolic system. Although this technique is described for linear systems, possible extension to nonlinear systems are also briefly discussed
Item Type:	Conference or Workshop Item
Copyright:	© 1990 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Stochastic Systems and Signals (SST)
Link to this item:	http://purl.utwente.nl/publications/30864
Official URL:	http://dx.doi.org/10.1109/CDC.1990.203585
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