Improved Adaptive Filter-Based Control of a Magnetostrictive Vibration Isolator

In this paper, an improved adaptive filtered-x normalized least-mean-square (FxNLMS) algorithm is proposed to achieve active microvibration isolation. A developed magnetostrictive device is used as an isolator to mitigate the microvibration. Whereas, the magnetostrictive material characterizes hysteresis. Although the constitutive and Bouc- Wen model were used to compensate the hysteresis, they are non-analytical with certain approximation. Otherwise, the Preisach model, a popular operator-based model, was also used to compensate the hysteresis. However, due to the double integrals in this model, the hysteresis identification and inversion process is complicated. Instead, this paper applies a modified Prandtl- Ishlinskii (PI) model to estimate and invert hysteresis, which is more simple but effective. The inverse hysteresis is then applied to compensate the magnetostrictive- induced hysteresis with conventional FxNLMS algorithm. Experimental results demonstrate that the improved FxNLMS algorithm enhance the performance of the microvibration isolation effectively.