Recursive Identification of Systems with Noninvertible Output Nonlinearities

The paper deals with the recursive identification of dynamic systems having noninvertible output characteristics, which can be represented by the Wiener model. A special form of the model is considered where the linear dynamic block is given by its transfer function and the nonlinear static block is characterized by such a description of the piecewise-linear characteristic, which is appropriate for noninvertible nonlinearities. The proposed algorithm is a direct application of the known recursive least squares method extended with the estimation of internal variables and enables the on-line estimation of both the linear block parameters and the parameters of some noninvertible nonlinearities and their changes. The feasibility of the proposed method is illustrated on examples of time-varying systems.

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