Identification Method for Systems with Zero-Memory Nonlinear Element

An iterative method is proposed for the identification of nonlinear systems from samples of inputs and outputs in the presence of noise. The model used for the identification consists of a no-memory gain (of an assumed polynomial form) followed by a linear discrete system. The parameters of the pulse transfer function of the linear system and the coefficients of the polynomial non-linearity are alternately adjusted to minimize a mean square error criterion. Digital computer simulations are included to demonstrate the feasibility of the technique.

An iterative method for the identification of nonlinear systems using a Hammerstein model

A method for system identification is proposed which is based on the error-correcting training procedure in learning machines, and is referred to as "learning identification." This learning identification is nondisturbing, is applicable to cases where the input signal is random and nonstationary, and can be completed within a short time, so that it may be used to identify linear quasi-time-invariant systems in which some parameters vary slowly in comparison with the time required for identification. This merit also makes it possible to eliminate noise disturbances by means of the moving average method. Computer simulation of the learning identification was carried out and the times required for identification were obtained for various cases. Some modifications of the learning identification were also investigated together with their computer simulations.

A learning method for system identification

A method is presented for the automatic identification of the unknown parameters of a class of nonlinear systems. The method is based on a modification of a steepest-descent type of adjustment technique which has proven useful in the identification of the unknown parameters of linear systems. Stability and convergence of the tracking model are assured by the proposed method.

Identification Method for Systems with Zero-Memory Nonlinear Element

References

An iterative method for the identification of nonlinear systems using a Hammerstein model

A learning method for system identification

An automatic identification technique for a class of nonlinear systems

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