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In this paper, a new neural-network-based hysteresis model is presented. First of all, a variable-power hysteretic operator is proposed via the characteristics of the motion point trajectory of hysteresis for magnetostrictive actuators. Based on the variable-power hysteretic operator, a basic hysteresis model is obtained. And then, a two-dimension input(More)
A new approach to constructing hysteretic operator is proposed in this paper. Based on the hysteretic operator, the input space of neural networks is expanded from 1-dimension to 2-dimension and the multi-value mapping of hysteresis is transformed into one-to-one mapping. Based on the expanded input space, a neural network is employed to approximate(More)
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