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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.

93B30System identification
93C10Nonlinear control systems
93C55Discrete-time control systems
93E24Least squares and related methods in stochastic control
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