Optimal recurrent algorithms for identification of nonstationary plants

Abstract Identification of static or dynamic linear plants with time-varying parameters is considered. The drift of parameters is described by difference equations. A recurrent identification algorithm having an asymptotically optimal rate of convergence is obtained. The algorithm is nonlinear if noises are non-Gaussian. Particular cases and extensions are discussed.

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