Active Vibration Control of Composite Structures Using MicroBlaze™ Soft Core Processor on Virtex-4 FPGA

Abstract

The present work investigates Multi -channel Active Vibration Control (AVC) of a composite research wing model and shell structure using modified Filtered ¥ Least Mean Square (F¥LMS) algorithm on Field Programmable Gate Arrays (FPGAs). AVC, using Digital Signal Processing (DSP) techniques are cost effective. But FPGAs, consuming small silicon area, have emerged as a dominant technology in embedded applications with potential features like high speed processing and low power consumption. Prominent features like high-speed parallel processing architecture along with hardware reconfigurability facilitates its usage to be wide spread in signal processing applications. An adaptive active vibration control system based on feed forward modified F¥LMS algorithm implemented on FPGA hardware is presented here. The results from the Multi channel real time AVC studies are brought out in the paper.

Experimental study on sliding mode variable structure control of active vibration isolation system of floating raft under multiple excitations

“…Substitute formula (7) into formula (6) to obtain the discrete control input voltage based on index reaching law uðkÞ ¼ ðCeBÞ À1 ðCe Á rðk þ 1Þ þ sðkÞ þ TsðÀeq à sgnðsðkÞÞ À qsðkÞÞ À CeAxðkÞÞ (8) To control buffeting of controller and the limit of input voltage, saturation function sat(s(k)) is adopted to substitute sgn(s(k)) in formula (8) satðsÞ ¼…”

“…Self-adaptive feedforward control method based on LMS algorithm has such advantages as simple algorithm structure, easy implementation, and strong stability, so it has been studied extensively. [2][3][4][5][6] Gao et al 2 carried out experimental study on the cRIO real-time control platform through Fx-LMS self-adaptive filtering algorithm and realized active control of double-deck vibration isolation platform by adopting self-adaptive algorithm. By taking piezoelectric rod as the active component, Li et al 3 constructed cube Stewart vibration isolation platform and adopted digital control system based on DSP and Fx-LMS self-adaptive algorithm for vibration control.…”

“…4 Chen et al 5 adopted self-adaptive feedforward method to the vibration isolation system of maglev vibration isolator for multifrequency active vibration isolation experiment. Prakash et al 6 studied the application of LMS algorithm in practice and achieved good results. 7,8 With regard to floating raft vibration isolation system, Chen 9 studied feedforward control by using Fx-LMS algorithm and pointed out the impact of sound feedback on reference signal in Fx-LMS algorithm.…”

“…Self-adaptive feedforward control method based on LMS algorithm has such advantages as simple algorithm structure, easy implementation, and strong stability, so it has been studied extensively. 2–6 Gao et al. 2 carried out experimental study on the cRIO real-time control platform through Fx-LMS self-adaptive filtering algorithm and realized active control of double-deck vibration isolation platform by adopting self-adaptive algorithm.…”

Wavelet transform and least square support vector machine for mechanical fault detection of an alternator using vibration signal

“…Wavelet coefficients cannot be directly used as inputs to a classifier, so a pre-processing stage is essential to prepare data for the classifier. 15 Feature extraction 16 is used in this research for determination of useful data from vibration signals of the alternator. The extracted features are used as inputs to the classifier for signal identification and fault classification.…”