Abstract

Using a combination of the pole placement and online empirical mode decomposition (EMD) methods, a new algorithm is proposed for adaptive active control of structural vibration. The EMD method is a time-frequency domain analysis method that can be used for nonstationary and nonlinear problems. Combining the EMD method and Hilbert transform, which is called Hilbert–Huang transform, achieves a method that can be implemented to extract instantaneous properties of signals such as structural response dominant instantaneous frequencies. In the proposed algorithm, these estimated instantaneous properties are utilized to improve the pole-placement method as an adaptive active control technique. The required active control gains are obtained using a genetic algorithm scheme, and optimal gains are calculated corresponding to preselected excitation frequencies. An algorithm is also introduced to choose excitation frequencies based on online EMD method resolution. In order to investigate the efficiency of the proposed method, some case studies that include a discrete model, continuous samples of beam and plate structures, and experimental cantilevered beam are carried out, and the results of the proposed method are compared with the preset (nonadaptive) optimal gains conditions.

References

1.
Boashash
,
B.
,
1992
, “
Estimating and Interpreting the Instantaneous Frequency of a Signal. II. Algorithms and Applications
,”
Proc. IEEE
,
80
(
4
), pp.
540
568
.
2.
Shi
,
D. F.
,
Wang
,
W. J.
, and
Qu
,
L. S.
,
2004
, “
Defect Detection for Bearings Using Envelope Spectra of Wavelet Transform
,”
ASME J. Vib. Acoust.
,
126
(
4
), pp.
567
573
.
3.
Cempel
,
C.
, and
Tabaszewski
,
M.
,
2007
, “
Multidimensional Condition Monitoring of Machines in Non-Stationary Operation
,”
Mech. Syst. Signal Process.
,
21
(
3
), pp.
1233
1241
.
4.
Bartelmus
,
W.
, and
Zimroz
,
R.
,
2009
, “
A New Feature for Monitoring the Condition of Gearboxes in Non-Stationary Operating Conditions
,”
Mech. Syst. Signal Process.
,
23
(
5
), pp.
1528
1534
.
5.
Chen
,
Z.
, and
Yang
,
Y.
,
2012
, “
Fault Diagnostics of Helicopter Gearboxes Based on Multi-Sensor Mixtured Hidden Markov Models
,”
ASME J. Vib. Acoust.
,
134
(
3
), p. 031010.
6.
Huang
,
N. E.
,
Shen
,
Z.
,
Long
,
S. R.
,
Wu
,
M. C.
,
Shih
,
H. H.
,
Zheng
,
Q.
,
Yen
,
N. C.
,
Tung
,
C. C.
, and
Liu
,
H. H.
,
1998
, “
The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis
,”
Proc. R. Soc. Lond. A
,
454
(
1971
), pp.
903
995
.
7.
Wu
,
Z.
, and
Huang
,
N. E.
,
2009
, “
Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method
,”
Adv. Adapt. Data Anal.
,
1
(
1
), pp.
1
41
.
8.
Torres
,
M. E.
,
Colominas
,
M. A.
,
Schlotthauer
,
G.
, and
Flandrin
,
P.
,
2011
, “
A Complete Ensemble Empirical Mode Decomposition With Adaptive Noise
,”
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
,
IEEE
,
New York
, pp.
4144
4147
.
9.
Nagarajaiah
,
S.
,
2009
, “
Adaptive Passive, Semiactive, Smart Tuned Mass Dampers: Identification and Control Using Empirical Mode Decomposition, Hilbert Transform, and Short-Term Fourier Transform
,”
Struct. Control Health Monit.
,
16
(
7–8
), pp.
800
841
.
10.
Narang
,
N.
,
Sharma
,
M. K.
, and
Vig
,
R.
,
2013
, “
Active Noise Control Using Intrinsic Mode Function Technique
,”
2013 5th International Conference on Computational Intelligence and Communication Networks (CICN)
,
IEEE
,
New York
, pp.
210
214
.
11.
Nie
,
Y.
,
Junsheng
,
C.
,
Yang
,
Y.
, and
Chen
,
J.
,
2013
, “
A Multichannel Active Noise Control System Based on Empirical Mode Decomposition
,” ,
32
(
20
), pp.
189
195
.
12.
Gupta
,
R.
, and
Ansell
,
P. J.
,
2017
, “
Closed-Loop Trailing-Edge Separation Control System Using Empirical Mode Decomposition
,”
AIAA J.
,
56
, pp.
121
131
.
13.
Kumar
,
R.
, and
Khan
,
M.
,
2007
, “
Pole Placement Techniques for Active Vibration Control of Smart Structures: A Feasibility Study
,”
ASME J. Vib. Acoust.
,
129
(
5
), pp.
601
615
.
14.
Razmjooy
,
N.
,
Madadi
,
A.
,
Alikhani
,
H. R.
, and
Mohseni
,
M.
,
2014
, “
Comparison of LQR and Pole Placement Design Controllers for Controlling the Inverted Pendulum
,” ,
3
(
2
), pp.
83
88
.
15.
Schmid
,
R.
,
Ntogramatzidis
,
L.
,
Nguyen
,
T.
, and
Pandey
,
A.
,
2014
, “
A Unified Method for Optimal Arbitrary Pole Placement
,”
Automatica
,
50
(
8
), pp.
2150
2154
.
16.
Brahma
,
S.
, and
Datta
,
B.
,
2009
, “
An Optimization Approach for Minimum Norm and Robust Partial Quadratic Eigenvalue Assignment Problems for Vibrating Structures
,”
J. Sound Vib.
,
324
(
3–5
), pp.
471
489
.
17.
Momeni Massouleh
,
S. H.
,
Hosseini Kordkheili
,
S. A.
, and
Navazi
,
H. M.
,
2018
, “
A Fast Online Bandwidth Empirical Mode Decomposition Scheme for Avoidance of the Mode Mixing Problem
,”
Proc. Inst. Mech. Eng. Part C
,
232
(
20
), pp.
3652
3674
.
18.
Rilling
,
G.
, and
Flandrin
,
P.
,
2008
, “
One or Two Frequencies? The Empirical Mode Decomposition Answers
,”
IEEE Trans. Signal Process.
,
56
(
1
), pp.
85
95
.
19.
Stepien
,
P.
,
2014
, “
Sliding Window Empirical Mode Decomposition-Its Performance and Quality
,”
EPJ Nonlinear Biomed. Phys.
,
2
(
1
), p.
14
.
20.
Huang
,
N. E.
,
2014
,
Hilbert-Huang Transform and Its Applications
, Vol.
16
,
World Scientific
,
Singapore
.
21.
Curtis
,
A.R.
1991
, “
An Application of Genetic Algorithms to Active Vibration Control
,”
J. Intell. Mater. Syst. Struct.
,
2
(
4
), pp.
472
481
.
22.
Abbasi
,
M.
, and
Markazi
,
A. H. D.
,
2014
, “
Optimal Assignment of Seismic Vibration Control Actuators Using Genetic Algorithm
,” ,
1
, pp.
24
31
.
23.
Ogata
,
K.
, and
Yang
,
Y.
,
2002
,
Modern Control Engineering
, Vol.
4
.
Prentice-Hall
,
India
.
You do not currently have access to this content.