Robust active control of noise and vibrations
Project members: P.R. Fraanje, M. Verhaegen
Our research on robust active control of noise and vibrations focuses
on the suppression of broadband stochastic disturbances (see e.g.
Figure 5). Until now active noise/vibration
control (ANVC) has been successfully applied to cancel harmonic
disturbances, e.g. in propeller aircrafts and air conditioning
systems. In most of these ANVC systems, the FilteredX LMS algorithm
is applied, because of its simplicity and adaptivity.
Figure 5:
Artist impression of a smart panel system, in which
disturbing vibrations are suppressed by controlling piezoelectric
actuators.

However, the control of broadband disturbances, e.g. in jet aircrafts
and roadtire/aerodynamic noise in cars, suffers to some important
problems, which has hold back from practical application:
 contrary to the case of harmonic disturbances, in the case of
broadband disturbances usually no reference signal which is highly
correlated with the disturbance is available;
 adaptive LMS algorithms, like FilteredX LMS converges very
slowly due to correlation in the broadband regression signal;
 the system to be controlled is usually an infinite dimensional
system, which yields high model orders in its finite order
approximation;
 the system, especially actuators and sensors, often suffer to
nonlinear behavior.
To solve these problems, we have proposed two solutions:
 an offline probabilistic control design method, which optimizes
the average performance over a stochastic model uncertainty set;
 an robust fast adaptive control design method, which is
basically a robust preconditioned version of the FilteredX LMS
algorithm.
Our research to improve the performance of the first method is on
controlrelevant (closedloop) identification of the model and
iterative identification and controller design. In cooperation with
the University of California, Los Angels, we investigate how to
improve the second method, such that performance bounds can be
guaranteed.
For large scale applications, e.g. in smart materials, with many
sensors and actuators, decentralized and distributed control methods
needs to be developed to reduce the complexity of the realtime
controller. Therefore a second main research goal is to design and
practically validate decentralized ANVC algorithms for broadband
disturbance suppression.
This project is done in cooperation with
TNOTPD.
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