Temperature dependent hysteresis modeling of a piezotube actuator using elman neural network

Mohammad Al Janaideh (1) , Mohammad Al Saaideh (2) , Micky Rakotondrabe (3)

1 Memorial University of Newfoundland - Memorial University of Newfoundland
2 University of Jordan
3 LGP - Laboratoire Génie de Production

In this study, the hysteresis nonlinearities of a piezotube actuator are investigated under different levels of surrounding temperature. The experimental results show that increasing of the surrounding temperature contributes to an increase in the output displacement of the piezotube actuator under the input range that is considered in the experimental tests. In this study, we develop a hysteresis model integrates the dead-zone operator with Elman Neural Network (ENN) to model the temperature-dependent hysteresis nonlinearities. The simulation results show that the proposed temperature-dependent hysteresis model accounts for the temperature effects on the voltage-to-displacement hysteresis nonlinearities. The results show that the proposed model can characterize the voltage-to-displacement hysteresis loops over different levels of surrounding temperature.

Mots clés: Hysteresis modeling; Piezotube actuator; Elman neural network

Domaines: Modélisation et simulation; Electronique

Mohammad Al Janaideh, Mohammad Al Saaideh, Micky Rakotondrabe. Temperature dependent hysteresis modeling of a piezotube actuator using elman neural network. Dynamic Systems and Control Conference, Oct 2019, Park city, United States. pp.1-7. ⟨hal-03103960⟩