Active vibration control and active noise control are both based on the same principles the main difference
being the type of actuators and transducers. These active control methods can be very effective at reducing vibration and
noise at low frequencies where most passive vibration and noise palliatives generally are rather ineffective. Active vibration
control and active noise control have the advantage of providing lightweight solutions for the attenuation of vibration and
noise albeit of some cost that can be significant. Active control methods are frequently employed within fields where weight
is an issue, typically aircraft structures.
Active vibration/noise control systems consist of three main components: a number of actuators (force generators
for vibration /loudspeakers for noise), a number of sensors (accelerometers/microphones) and finally a multi-channel digital
input/output system with signal processing capable of operating in real-time. The principle of operation is that active control
system, based on the sensor input and a mathematical model of the system, generates an anti vibration/noise field, that is,
a field that as closely as possible is identical to the uncontrolled vibration/noise field but with opposite phase.
If these two vibration/noise fields (the uncontrolled and the actuator generated) were identical in amplitude and had exact
the opposite phase, then the addition of the two fields would lead to complete elimination of the vibrations/noise levels.
The principle can be illustrated for a simple beam that is excited by various forces and moments, see Fig.
1. These forces and moments will for, this example, excite all the modes of the beam but predominantly the lowest three modes.
The response of the uncontrolled system is shown in Fig. 2 top graph. As the uncontrolled vibration response is dominated
by the three lowest modes the active vibration control system will for this example be based on three force actuators. The
vibration field generated by the actuators is shown in Fig. 2 middle graph. The result of adding these two vibration fields
is shown in Fig. 2 bottom graph. As can be seen, the vibration field is not reduced to zero as an active vibration control
system can at the best only control as many modes as there are actuators. The residual vibration level will be due to uncontrolled
contributions from higher order modes as well as imperfections in generating the perfect anti-vibration field.
A multiple input – multiple output (MIMO) control algorithm operating in the time domain can either
be based on a feed-back strategy (state-space model) or a feed-forward strategy (adaptive digital filters). Fig.3 shows the
principle in an MIMO feed-forward system that is based on the MIMO filtered, x-LMS
algorithm. This algorithm seeks to minimise the square of the response signals by adjusting the filter coefficients, wj , that controls the output of the actuators. The digital filters,
fi,j , (typically IIR filters) corresponds to the mathematical
model of the system given as transfer functions between actuators and sensors positions. Fig. 4 shows an example of an IIR
filter fitted to match a measured transfer function.
Fig. 5 shows electro-dynamic shakers connected to a helicopter tail for an active vibration control experiment.
Fig. 6 shows the effect on the response of two accelerometers of engaging the active vibration control system. As the blue
signal initially dominates the cost function, the red signal is not reduced until the two signals have are at the same level.
Fig. 7 shows the spectrum of the blue signal (from Fig. 6) with and without active vibration control. As the active vibration
control algorithm in this case only controlled the fundamental frequency, the overall vibration level could only be reduced
to a level where the first harmonic becomes dominant.
