Adaptive random control of a two-axis redundantly actuated electro-hydraulic shaking table

Abstract

An adaptive random control method is presented for a two-axis redundantly actuated electro-hydraulic shaking table system to replicate the reference acceleration power spectral density (PSD). The redundant force controller is developed to reduce the cross-coupling among the actuators. The offline iterations are implemented in conventional random control to compensate for the changes in the frequency response function of the system. Stability and responsiveness of control are determined by operator-selected parameters. In adaptive random control, the reference PSD is transformed into time domain histories by filtering white noise. The adaptive finite impulse response (FIR) filters are used to model and track the inverse system online. The weights of the FIR filters are updated by the forgetting factor recursive least-squares algorithm. The time histories are corrected by the copy of the inverse model. Experimental results obtained in step response and PSD replication demonstrate the effectiveness of the proposed control method.