Traditional passive nonlinear isolators have been paid much attention in recent literatures due to their excellent performance compared to linear vibration isolators. However, they are incapable of dealing with varying conditions such as changing excitation frequency due to the nonadjustable negative stiffness. To solve this drawback, a new approach to achieve variable negative stiffness is proposed in this paper. The negative stiffness is realized by an electromagnetic asymmetric magnetic tooth structure and can be changed by adjusting the magnitude of the input direct current. Analytical model of the electromagnetic force is built and simulations of magnetic field are conducted to validate the negative stiffness. Then the EATS is applied to vibration isolation and an electromagnetic vibration isolator is designed. Finally, a series of tests are conducted to measure the negative stiffness experimentally and confirm the effect of the EATS in vibration isolation.

Simultaneous perturbation stochastic approximation (SPSA) algorithm, an algorithm without secondary path modeling, has been applied to active noise control by some researchers. Some extended versions of this algorithm have been also developed to improve its performance. However, these existing algorithms are mostly dedicated to controlling the periodic noise instead of the broadband noise. In particular, background noise is not taken into account when SPSA algorithms are applied to control broadband noise. In this paper, an algorithm combining the cost function with the SPSA algorithm to control broadband noise has been proposed. The suggested cost function is an inner product of the estimated cross-correlation function between a reference vector and the error signal. The elements of the reference vector are composed of the reference signals at different times. Moreover, the algorithm analysis is performed and the numerical simulations are carried out to demonstrate the validity of the proposed algorithm. The results illustrate that the proposed algorithm can effectively reduce broadband noise when interference noise exists in the control system. Furthermore, the proposed algorithm has better convergence performance than other SPSA algorithms.

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