Adaptive filtered x-least mean square algorithm with improved convergence for resonance suppression

Abstract

The existence of the resonance is usually a trouble causing instability for most elastic drive systems. Generally, the measurement of original resonance of load side in a drive system is a direct solution for resonance suppression, but exact data are difficult to come by, such as torsional torque, load speed and disturbance torque. Therefore, a developed method for resonance suppression based on adaptive filtered x-least mean square algorithm with improved convergence is presented in this research. The proposed method obtains the resonance iteratively and reduces the significant resonance oscillations through a finite impulse response filter adapted by the least mean square error principle. In order to tackle the convergence speed problem caused by the high dynamics of the forward path model, another finite impulse response filter is inserted into the control structure to smooth the current control reference signal and the speed error signal, so that the dynamics features of the forward path model are improved. Furthermore, a filtered x-least mean square control structure for elastic drive systems is also developed. From the simulation and experimental results, the resonance is more effectively suppressed with proposed modified filtered x-least mean square structure compared with notch filters, and the inserted finite impulse response improves the convergence speed.

Resonance Suppression for Hydraulic Servo Shaking Table Based on Adaptive Notch Filter

“…Wang et al adopted the modi ed resonance frequency detection and reduction method based on an adaptive notch lter to extend the middle frequency range of an industrial servo system [17]. Wang et al presented an improved adaptive ltered x-LMS algorithm to suppress the resonance in the elastic drive system, which proves the better resonance suppression e ect as well as convergence speed than the conventional method [18]. Rahman put forward a discrete time adaptive compensator based on an autotuning algorithm to suppress the time-varying resonance characteristics of a hard drive servo system [19].…”

Study on the Resonant Suppression of Electrohydraulic Servo Shaking Table of a 2‐Mass Dynamic System

“…In the servo system, change of natural frequency, load characteristic, and additional characteristic can change the frequency and amplitude of the resonance, so the adaptive algorithm is put forward to suppress the resonance. A developed method for resonant suppression based on adaptive filtered x-least mean square algorithm was presented by Wang et al, which obtained the resonance iteratively and reduced the significant resonant oscillations using a finite impulse response filter, which was adapted by the least mean square error principle [12]. Kang and Kim proposed the method of an adaptive digital notch filter that could identify the resonant frequency of the actuator quickly and adjust automatically its center frequency [13].…”