Acceleration harmonic identification for an electro-hydraulic servo shaking table based on the normalized least-mean-square adaptive algorithm

Abstract

For an electro-hydraulic servo shaking table, there are nonlinearities, which cause acceleration harmonic distortion when they corresponds to a sine acceleration excitation signal. The work here is to develop an acceleration harmonic identification algorithm by using the normalized least-mean-square (LMS) adaptive algorithm, whose weights are updated by the error between the acceleration response and the estimated acceleration signal. The input vector is generated by the reference harmonics and the [Formula: see text] phase shift. When the identification algorithm converges, the amplitude and phase of each harmonic can be computed from the weight vector. Experimental results show that the proposed harmonic identification has good real-time performance and a fast convergence rate, and it can identify harmonics on-line with high precision both in amplitude and in phase.