The Fiber Bragg Grating(FBG) sensors are applied to Giant Magnetostrictive Actuator(GMA) to obtain the multi-physics field factors, which are the basis of data driven model. The real working circumstance of GMA is complex and nonlinear, and the traditional theoretical physics model of GMA cannot satisfy it. Hence, the multi-physics field factors of the components of GMA in real working process are gathered real-time by FBG sensors, such as temperature of Giant Magnetostrictive Material(GMM) stick and coil, displacement and vibration of GMM stick, current of coil etc, which are utilized to represent the strong nonlinear characteristics of GMA. Furthermore, the data driven model of GMA is built with the Least Squares Support Vector Machine(LS-SVM) method based on multi-physics field factors. The performance of the novel GMA model is evaluated by experiment, its maximum error is 1.1% with frequency range from 0 to 1000Hz and temperature range from 20°C to 100°C.
In this paper, a new means of measuring the displacement of GMA (Giant Magnetostrictive Actuator) based on FGB (Fiber Bragg Grating) sensor is proposed, experimental results confirmed that FGB sensor can measure the displacement of GMA in different frequencies and achieve good results. In addition a modified Bouc-Wen model is presented to describe the GMA, the proposed model can describe the asymmetric hysteresis of GMA from 1 Hz to 100 Hz well, and DE(Differential Evolution) algorithm is used for adaptive identification of the GMA system, the algorithm has fast convergence and high accuracy. Finally, it verifies that the identification model fits the experimental data well.