Proc. SPIE. 7645, Industrial and Commercial Applications of Smart Structures Technologies 2010
KEYWORDS: Actuators, Detection and tracking algorithms, Modulation, Signal attenuation, Digital filtering, Control systems, Electronic filtering, Systems modeling, Model-based design, Nonlinear control
This research investigates a supporting structure with smart struts under a vibratory load. In the case of most rotorcraft,
structure-borne noise and vibration transmitted from the gearbox contains multiple spectral elements and higher
frequencies, which include gear mesh frequencies and their side bands. In order to manage this issue, significant research
have been devoted to active smart struts which have tunable stiffness such that a higher level of attenuation is possible.
However, present techniques on active control are restricted mostly to the control of single or multiple sinusoids and thus
these are not applicable to manage modulated and multi-spectral signals. Therefore, enhanced control algorithms are
required in order to achieve simultaneous attenuation of gear mesh frequencies and their side bands. Proposed algorithms
employing two nonlinear methods and one model-based technique are examined in this study. Their performance is
verified by comparing with conventional algorithms. Moreover, these algorithms are implemented to exhibit whether
they are feasible to narrowband or broadband control through experiments with a single smart strut. Novel
methodologies are expected to be applied to several active vibration and noise control practices such as vehicles and
other engineering structures.
The primary objective of this research is to develop novel model-based multispectral controllers for smart material
systems in order to deal with sidebands and higher harmonics and with several frequency components simultaneously.
Based on the filtered-X least mean square algorithm, it will be integrated with a nonlinear model-based controller called
model predictive sliding mode control. Their performance will be verified in simulation and with various applications
such as helicopter cabin noise reduction. This research will improve active vibration and noise control systems used in
engineering structures and vehicles by effectively dealing with a wide range of multispectral signals.