Direct recursive identification of the Preisach hysteresis density function

• Novel direct method of recursive identification of the Preisach hysteresis density function is proposed.
• The online estimation is based on the output increment error.
• The Discrete Dynamic Preisach model which is a state-space realization of the classical scalar Preisach is used.
• The convergence of the estimate of different Gaussian mixtures of hysterons is shown for a low-pass filtered white-noise input.

In this paper, a novel direct method of recursive identification of the Preisach hysteresis density function is proposed. Using the discrete dynamic Preisach model, which is a state-space realization of the classical scalar Preisach model, the method is designed based on the output increment error. After giving the general formulation, the identification scheme implemented for a discretized Preisach plane is introduced and evaluated through the use of numerical simulations. Two cases of Gaussian mixtures are considered for mapping the hysteresis system to be identified. The parameter convergence is shown for a low-pass filtered white-noise input. Further, the proposed identification method is applied to a magnetism-related application example, where the flux linkage hysteresis of a proportional solenoid is assumed from the measurements, and then the inverse of a standard demagnetization procedure is utilized as the identification sequence.