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Identification of linear parameter varying models. (English) Zbl 1007.93022

This paper deals with the identification of discrete-time nonlinear systems known as linear parameter varying system. Inputs, outputs and the scheduling parameters are directly measured, and a form of the functional dependence of the system coefficients on the parameters is known. The identification problem is reduced to a linear regression that provides compact formulae for the corresponding least mean square and recursive least-squares algorithms. Conditions on the persistency of excitation in terms of the inputs and scheduling parameters trajectories are also given when the functional dependence is of polynomial type. The method is illustrated with a simulation example using two different trajectories.

MSC:

93B30 System identification
93C10 Nonlinear systems in control theory
93C55 Discrete-time control/observation systems
93E24 Least squares and related methods for stochastic control systems
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References:

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