Hybrid Filtered-x Adaptive Vibration Control with Internal Feedback and Online Identification

Abstract

Active control is an effective way to suppress low-frequency mechanical vibration. However, with applications to submarine equipment, there are still some shortcomings due to vibration coupling and multifrequency complex excitation. In this paper, a novel hybrid improved adaptive control strategy, feedback and online identification filtered-x LMS, namely, FOFxlms, is proposed, which introduces the residual errors to correct variable step-size, uses the estimated primary path to improve online identification, and applies internal feedback to compensate for the feedforward control. Then the FOFxlms algorithm is applied to a double-layer vibration isolation system of submarine rotating equipment, and the simulation results show that the normalized variable step-size with residual error can effectively improve convergence speed, the internal feedback can efficaciously compensate for steady-state control accuracy, and the online identification can dynamically identify the time-varying characteristics of the secondary path. The vibration reduction efficiency of Fxlms, FFxlms, and FOFxlms increases for the fundamental frequency vibration; the control effect and convergence speed are also enhanced in turn.