In this paper, the sequential quadratic programming (SQP) method is used to calculating parameter optimization of the tuned mass damper (TMD) for three-degree-offreedom vibration systems. The following concluding remarks have been reached:
- If the TMD is attached to the vibration source (excited force or kinematical excitement), the effect of vibration reduction will be achieved globally.
- If the TMD is attached to the place far away from the vibration source, the effect
of vibration reduction will be achieved in the upper masses from the position of TMD.
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Volume 35 Number 3
3
Vietnam Journal of Mechanics, VAST, Vol. 35, No. 3 (2013), pp. 215 – 224
PARAMETER OPTIMIZATION OF TUNED MASS
DAMPER FOR THREE-DEGREE-OF-FREEDOM
VIBRATION SYSTEMS
Nguyen Van Khang1,∗, Trieu Quoc Loc2, Nguyen Anh Tuan2
1 Hanoi University of Science and Technology, Vietnam
2 National Institute of Labour Protection, Vietnam
∗E-mail: khang.nguyenvan2@hust.edu.vn
Abstract. There are problems in mechanical, structural and aerospace engineering that
can be formulated as Nonlinear Programming. In this paper, the problem of parameters
optimization of tuned mass damper for three-degree-of-freedom vibration systems is in-
vestigated using sequential quadratic programming method. The objective is to minimize
the extreme vibration amplitude of vibration models. It is shown that the constrained
formulation, that includes lower and upper bounds on the updating parameters in the
form of inequality constraints, is important for obtaining a correct updated model.
Keywords : Vibration, tuned mass damper, optimal design, nonlinear programming.
1. INTRODUCTION
Optimal design of multibody systems is characterized by a specific kind of optimiza-
tion problem. Generally, an optimization problem is formulated to determine the design
variable values that will minimize an objective function subject to constraints. Addition-
ally, for many engineering applications, multibody analysis routine are used to calculate
the kinematic and dynamic behavior of the mechanical design. As a result, most objective
function and constraint values follow from the numerical analysis.
Use of the tuned mass damper (TMD) as an independent means of vibration control
is especially important, particularly in the case where it is almost the only or main means
of vibration protection [1-6]. A tuned mass damper, also known as an active mass damper
(AMD) or harmonic absorber, is a device mounted in structures to reduce the amplitude of
vibrations. Its application can prevent discomfort, damage, or outright structural failure.
It is frequently used in power transmission, automobiles, machine and buildings.
In this paper we consider a problem of parameter optimization of tuned mass damper
for three-degree-of-freedom vibration systems using sequential quadratic programming
method [7-12].
216 Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan
2. REVIEW OF SEQUENTIAL QUADRATIC
PROGRAMMING METHOD
The sequential quadratic programming, or called SQP, is an efficient and powerful
algorithm to solve nonlinear programming problems. The method has a theoretical basis
that is related to (1) the solution of a set of nonlinear equations using Newton’s method,
and (2) the derivation of simultaneous nonlinear equations using Kuhn–Tu¨cker conditions
to the Lagrangian of the constrained optimization problem. In this section we review some
basic concepts of SQP method [7-10] for understanding the parameter optimization of the
TMD installed in vibration systems.
Consider a nonlinear optimization problem with equality constraints:
Find x which minimizes f(x)
subject to
hk(x) = 0, k = 1, 2, . . . , p. (1)
The Lagrange function L(x,λ), for this problem is
L(x,λ) = f(x) +
p∑
k=1
λkhk(x) = f(x) + λ
Th(x), (2)
where λk is the Lagrange multiplier for the equality constraint hk. The Kuhn–Tu¨cker
necessary conditions can be stated as
∇xL = 0 ⇒ ∇f(x) +
p∑
k=1
λk∇hk = 0 or ∇f(x) + λ
Th(x) = 0, (3)
∇λL = 0 ⇒ hk(x) = 0, k = 1, 2, . . . , p or h(x) = 0. (4)
Eqs. (3) and (4) represent a set of n + p nonlinear equations with n + p unknowns
(xi, i = 1, 2, . . . , n and λk, k = 1, 2, . . . , p). These nonlinear equations can be solved using
Newton’s method. For convenience, we rewrite Eqs. (3) and (4) as
b(y) = 0, (5)
where
b =
{
∇L
h
}
(n+p)×1
, y =
{
x
λ
}
(n+p)×1
, 0 =
{
0
0
}
(n+p)×1
. (6)
According to Newton’s method, the solution of Eqs. (5) can be found iteratively as[
∇2xL(yi) J
T
h (xi)
Jh(xi) 0
]{
∆xi
∆λi
}
= −
{
∇xL(yi)
h(xi)
}
, (7)
and
xi+1 = xi +∆xi, λi+1 = λi +∆λi. (8)
The first set of equations in (7) can be written separately as
∇
2
xL(yi)∆xi + J
T
h (xi)∆λi = −∇xL(yi) (9)
Using Eq. (8) for ∆λi and Eq. (3) for ∇xL(yi), Eq. (9) can be expessed as
∇
2
xL(yi)∆xi + J
T
h (λi+1 − λi) = −∇f(xi)− J
T
h (xi)λi, (10)
Parameter optimization of tuned mass damper for three-degree-of-freedom vibration systems 217
which can be simplified to obtain
∇
2
xL(yi)∆xi + J
T
h (xi)λi+1 = −∇f(xi). (11)
Eq. (11) and the second set of equations in (7) can now be combined as[
∇2xL(yi) J
T
h (xi)
Jh(xi) 0
]
j
{
∆xi
λi+1
}
= −
{
∇f(xi)
h(xi)
}
. (12)
Eqs. (12) can be solved to find the change in the design vector ∆xi and the new
values of the Lagrange multipliers, λi+1. The iterative process indicated by Eq. (12) can
be continued until convergence is achieved.
Now consider the following quadratic programming problem:
Find d = ∆x that minimizes the quadratic objective function
Q(d) = ∇xf(xi)
Td+
1
2
dT∇2xL(xi,λi)d, (13)
subject to the linear equality constraints
hk(xi) +∇h
T
k (xi)d = 0, k = 1, 2, . . . , p ⇒ h(xi) + Jh(xi)d = 0. (14)
The Lagange function L˜, corresponding to the problem of Eqs. (13) and (14) is given by
L˜(d,λ) = ∇xf(xi)
Td+
1
2
dT∇2xL(xi,λi)d+ λ
T [h (xi) + Jh (xi)d] . (15)
The Kuhn – Tu¨cker necessary conditions can be stated as
∇xf(xi) +∇
2
xL(xi,λi)d+ J
T
h (xi)λ = 0, (16)
h(xi) + Jh(xi)d = 0. (17)
The Eqs. (16) and (17) can be combined in the following matrix form as[
∇2xL(yi) J
T
h (xi)
Jh(xi) 0
]
j
{
di
λi
}
= −
{
∇f(xi)
h(xi)
}
. (18)
Eq. (18) can be identified to be same as Eq. (12) in matrix form. This shows that the
orginal problem of Eq. (1) can be solved iteratively by solving the quadratic programming
problem defined by Eq. (13).
In fact, when inequality constraints are added to the original problem, the quadratic
programming problem of Eqs. (13) and (14) becomes
Find x which minimizes
Q(d) = (∇f(xi))
Td+
1
2
dT∇2xL(xi,λi,µi)d, (19)
subject to
hk(xi) + (∇hk(xi))
Td = 0, k = 1, 2, . . . , p (20)
gj(xi) + (∇gj(xi))
Td ≤ 0, j = 1, 2, . . . , m (21)
with the Lagrange function given by
L(x,λ,µ) = f(x) +
p∑
k=1
λkhk(x) +
m∑
j=1
µjgj(x) = f(x) + λ
Th(x) + µTg(x) (22)
218 Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan
Since the minimum of the augmented Lagrange function is involved, the sequential
quadratic programming method is also known as the projected Lagrangian method.
3. CALCULATING OPTIMAL PARAMETERS OF TMD FOR THE
THREE-DEGREE-OF-FREEDOM VIBRATION SYSTEMS
In this section we study the influence of installed position of TMD on the behaviour
of three-degree-of-freedom vibration systems using the sequential quadratic programming
algorithm.
3.1. Vibration equation of system with the excited harmonic force at the
mass m1
Consider a damped linear vibration system of three-degree-of-freedom as shown in
Fig. 1a. The vibrating system has three masses m1, m2, m3; stiffness coefficients, respec-
tively, k1, k2, k3 and viscous coefficients, respectively, c1, c2, c3; the mass m1 is excited by
harmonic force F (t) = F0 cos(Ωt). The motion equations of the system have the following
form
m1y¨1 + (c1 + c2)y˙1 − c2y˙2 + (k1 + k2)y1 − k2y2 = F0cos(Ωt)
m2y¨2 − c2y˙1 + (c2 + c3)y˙2 − c3y˙3 − k2y1 + (k2 + k3)y2 − k3y3 = 0
m3y¨3 − c3y˙2 + c3y˙3 − k3y2 + k3y3 = 0
. (23)
a) b) c) d)
Fig. 1. The system of three-degree-of-freedom under excited force at m1
a) Primary system without TMD; b) System with TMD at m1
c) System with TMD at m2; d) System with TMD at m3
The steady-state response of the system has the form
y(t) = a cos(Ωt) + b sin(Ωt) (24)
with
y(t) =
y1(t)y2(t)
y3(t)
; a0 =
a01a02
a03
;b0 =
b01b02
b03
.
Parameter optimization of tuned mass damper for three-degree-of-freedom vibration systems 219
From Eq. (23) and Eq. (24), comparing coefficients of cos(Ωt) and sin(Ωt), we get
the system of linear algebraic equations for unknown elements of vectors a and b
(k1 + k2 −m1Ω
2)a01 + (c1 + c2)Ωb01 − k2a02 − c2Ωb02 = F0
−(c1 + c2)Ωa01 + (k1 + k2 −m1Ω
2)b01 + c2Ωa02 − k2b02 = 0
−k2a01 − c2Ωb01 + (k2 + k3 −m2Ω
2)a02 + (c2 + c3)Ωb02 − k3a03 − c3Ωb03 = 0
c2Ωa01 − k2b01 − (c2 + c3)Ωa02 + (k2 + k3 −m2Ω
2)b02 + c3Ωa03 − k3b03 = 0
−k3a02 − c3Ωb02 + (k3 −m3Ω
2)a03 + c3Ωb03 = 0
c3Ωa02 − k3b02 − c3Ωa03 + (k3 −m3Ω
2)b03 = 0
. (25)
By solving the system of Eqs. (25), we receive the values of elements a0i, b0i
(i = 1, 2, 3) of vectors a0 and b0. For numeric calculation, the values of the coefficients
are given as
m1 = m2 = m3 =100 kg, k1 = k2 = k3 = 10
5 N/m, c1 = c2 = c3 = 1000 Ns/m,
Ω = 47 rad/s, F (t) = 10 cos(47t).
3.2. Installation positions of TMD
a) System installed TMD in m1
As the first variant to quench vibrations of the system, we installed TMD with mass
mtc, spring stiffness ktc and viscous resistance ctc on mass m1 (Fig. 1b). The equation of
the system oscillations
m1y¨1 + (c1 + c2 + ctc)y˙1 − c2y˙2 − ctcy˙tc + (k1 + k2 + ktc)y1 − k2y2 − ktcytc = F0 cos(Ωt)
m2y¨2 − c2y˙1 + (c2 + c3)y˙2 − c3y˙3 − k2y1 + (k2 + k3)y2 − k3y3 = 0
m3y¨3 − c3y˙2 + c3y˙3 − k3y2 + k3y3 = 0
mtcy¨tc − ctcy˙1 + ctcy˙tc − ktcy1 + ktcytc = 0
(26)
The steady-state response of the system has the form
y(t) = a cos(Ωt) + b sin(Ωt) (27)
where
y(t) =
y1(t)
y2(t)
y3(t)
ytc(t)
; a =
a1
a2
a3
atc
;b =
b1
b2
b3
btc
From Eqs. (26)-(27), comparing coefficients of cos(Ωt) and sin(Ωt) we get the system
of linear algebraic equations for unknown elements of vectors a and b
(k1 + k2 + ktc −m1Ω
2)a1 + (c1 + c2 + ctc)Ωb1 − k2a2 − c2Ωb2 − ktcatc − ctcΩbtc = F0
−(c1 + c2 + ctc)Ωa1 + (k1 + k2 + ktc −m1Ω
2)b1 + c2Ωa2 − k2b2 + ctcΩatc − ktcbtc = 0
−k2a1 − c2Ωb1 + (k2 + k3 −m2Ω
2)a2 + (c2 + c3)Ωb2 − k3a3 − c3Ωb3 = 0
c2Ωa1 − k2b1 − (c2 + c3)Ωa2 + (k2 + k3 −m2Ω
2)b2 + c3Ωa3 − k3b3 = 0
−k3a2 − c3Ωb2 + (k3 −m3Ω
2)a3 + c3Ωb3 = 0
c3Ωa2 − k3b2 − c3Ωa3 + (k3 −m3Ω
2)b3 = 0
−ktca1 − ctcΩb1 + (ktc −mtcΩ
2)atc + ctcΩbtc = 0
ctcΩa1 − ktcb1 − ctcΩatc + (ktc −mtcΩ
2)btc = 0
. (28)
Solving the system of Eqs. (28), we receive the elements ai, bi (i = 1, 2, 3) of vectors
a and b.
220 Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan
For optimization problems, there is an optimization criterion (i.e. evaluation func-
tion) that has to be minimized or maximized. Here we must find the optimal values mtc,
ktc, ctc of TMD in order to minimize the expression of vibration amplitude of m1
R1 =
√
a21 + b
2
1,
with boundary constraints
5 ≤ mtc(kg) ≤ 10; 1000 ≤ ktc(N/m) ≤ 100000; 5≤ ctc(Ns/m) ≤ 1000.
Using the sequential quadratic programming algorithm in MAPLE software, we can
quickly and conveniently calculate the optimal parameters for TMD
R1 = 0.00000451601155 m; ktc = 22099.62597299 N/m; ctc = 5 Ns/m;mtc = 10 kg.
Some calculating results are provided in Tab. 1 and in Fig. 2.
Table 1. Effective vibration reduction system under excited force at m1
before and after installing TMD at m1
Location
Vibration amplitude (m) Efficient vibration damping (%)
Without TMD With TMD increase Reduced
m1 0.0000653278 0.000004516 93.08
m2 0.0000393333 0.000002719 93.08
m3 0.0000335052 0.000002316 93.08
Fig. 2. Amplitude of three degrees of freedom system under excited force at m1
before and after installing TMD at m1
Parameter optimization of tuned mass damper for three-degree-of-freedom vibration systems 221
b) System installed TMD in m2
As second variant to quench vibrations of the system, we installed TMD with mass
mtc, spring stiffness, ktc and viscous resistance, ctc on mass m1 (see Fig. 1c). The vibration
equations of the system have following form
m1y¨1 + (c1 + c2)y˙1 − c2y˙2 + (k1 + k2)y1 − k2y2 = F0 cos(Ωt)
m2y¨2 − c2y˙1 + (c2 + c3 + ctc)y˙2 − c3y˙3 − ctcy˙tc − k2y1 + (k2 + k3 + ktc)y2 − k3y3 − ktcytc = 0
m3y¨3 − c3y˙2 + c3y˙3 − k3y2 + k3y3 = 0
mtcy¨tc − ctcy˙2 + ctcy˙tc − ktcy2 + ktcytc = 0
(29)
From Eq. (27) and Eq. (29), comparing coefficients of cos(Ωt) and sin(Ωt) we get
the system of linear algebraic equations for unknown elements of vectors a and b
(k1 + k2 −m1Ω
2)a1 + (c1 + c2)Ωb1 − k2a2 − c2Ωb2 = F0
−(c1 + c2)Ωa1 + (k1 + k2 −m1Ω
2)b1 + c2Ωa2 − k2b2 = 0
−k2a1 − c2Ωb1 + (k2 + k3 + ktc −m2Ω
2)a2 + (c2 + c3 + ctc)Ωb2 − k3a3 − c3Ωb3 − ktcatc − ctcΩbtc = 0
c2Ωa1 − k2b1 − (c2 + c3 + ctc)Ωa2 + (k2 + k3 + ktc −m2Ω
2)b2 + c3Ωa3 − k3b3 + ctcΩatc − ktcbtc = 0
−k3a2 − c3Ωb2 + (k3 −m3Ω
2)a3 + c3Ωb3 = 0
c3Ωa2 − k3b2 − c3Ωa3 + (k3 −m3Ω
2)b3 = 0
−ktca2 − ctcΩb2 + (ktc −mtcΩ
2)atc + ctcΩbtc = 0
ctcΩa2 − ktcb2 − ctcΩatc + (ktc −mtcΩ
2)btc = 0
(30)
Solving the system of Eqs. (30), we receive the elements ai, bi (i = 1, 2, 3) of vectors
a and b. Thus, to minimize the vibration amplitude of m2 we must find optimal values
mtc, ktc, ctc of TMD to minimize the expression R2 =
√
a22 + b
2
2 with boundary constraints
5 ≤ mtc (kg) ≤ 10; 1000≤ ktc (N/m) ≤ 100000; 5≤ ctc (Ns/m) ≤ 1000.
Using SQP, we find the optimal parameters for TMD
R2 = 0.00000485578798 m; ktc = 22099.07992772 N/m; ctc = 5 Ns/m;mtc = 10 kg.
Some calculating results are shown in Tab. 2 and in Fig. 3.
Table 2. Effective vibration reduction system under excited force at m1
before and after installing TMD at m2
Location
Vibration amplitude (m) Efficient vibration damping (%)
Without TMD With TMD increase reduced
m1 0.0000653278 0.0000992695 51.95
m2 0.0000393333 0.0000048558 87.65
m3 0.0000335052 0.0000041363 87.65
222 Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan
Fig. 3. Vibration amplitude of system under excited force at m1
before and after installing TMD at m2
c) System installed TMD in m3
As third variant to quench vibrations of the system, we installed TMD with mass
mtc, spring stiffness, ktc and viscous resistance, ctc on mass m3 (see Fig. 1d).
The equation of the system oscillations
m1y¨1 + (c1 + c2)y˙1 − c2y˙2 + (k1 + k2)y1 − k2y2 = F0 cosΩt
m2y¨2 − c2y˙1 + (c2 + c3)y˙2 − c3y˙3 − k2y1 + (k2 + k3)y2 − k3y3 = 0
m3y¨3 − c3y˙2 + (c3 + ctc)y˙3 − ctcy˙tc − k3y2 + (k3 + ktc)y3 − ktcytc = 0
mtcy¨tc − ctcy˙3 + ctcy˙tc − ktcy3 + ktcytc = 0
. (31)
From Eq. (27) and Eq. (31), comparing coefficients of cos(Ωt) and sin(Ωt) we get
the system of linear algebraic equations for unknown elements of vectors a and b
(k1 + k2 −m1Ω
2)a1 + (c1 + c2)Ωb1− k2a2 − c2Ωb2 = F0
−(c1 + c2)Ωa1 + (k1 + k2 −m1Ω
2)b1 + c2Ωa2 − k2b2 = 0
−k2a1 − c2Ωb1 + (k2 + k3 −m2Ω
2)a2 + (c2 + c3)Ωb2− k3a3 − c3Ωb3 = 0
c2Ωa1 − k2b1 − (c2 + c3)Ωa2 + (k2 + k3 −m2Ω
2)b2 + c3Ωa3 − k3b3 = 0
−k3a2 − c3Ωb2 + (k3 + ktc −m3Ω
2)a3 + (c3 + ctc)Ωb3 − ktcatc − ctcΩbtc = 0
c3Ωa2 − k3b2 − (c3 + ctc)Ωa3 + (k3 + ktc −m3Ω
2)b3 + ctcΩatc − ktcbtc = 0
−ktca3 − ctcΩb3 + (ktc −mtcΩ
2)atc + ctcΩbtc = 0
ctcΩa3 − ktcb3 − ctcΩatc + (ktc −mtcΩ
2)btc = 0
. (32)
Solving the system of Eqs. (32), and identify the elements ai, bi (i = 1, 2, 3) of vectors
a and b. Thus, to minimize the vibration amplitude of m3 we must find optimal values
mtc, ktc, ctc of TMD to minimize the expression R3 =
√
a23 + b
2
3 with boundary constraints
5 ≤ mtc (kg) ≤ 10; 1000≤ ktc (N/m) ≤ 100000; 5≤ ctc (Ns/m) ≤ 1000.
Using SQP, we find the optimal parameters for TMD
R3 = 0.00000266217877 m; ktc = 22106.994965140063 N/ m; ctc = 5 Ns/ m;mtc = 10 kg.
Some calculating results are shown in Tab. 3 and in Fig. 4.
Parameter optimization of tuned mass damper for three-degree-of-freedom vibration systems 223
Table 3. Effective vibration reduction system under excited force at m1
before and after installing TMD at m3
Location
Vibration amplitude (m) Efficient vibration damping (%)
Without TMD With TMD increase reduced
m1 0.0000653278 0.0000471 27.88
m2 0.0000393333 0.0000514 30.64
m3 0.0000335052 0.00000266 92.05
Fig. 4. Vibration amplitude of system under excited force at m1
before and after installing TMD at m3
From the simulation results in Figs 1-4 we have the following observations: When
the TMD is installed on mass m1, the vibration amplitudes of masses m1, m2, m3 are
significantly reduced. When the TMD is installed on mass m2, the vibration amplitude
of masses m2 and m3 are significantly reduced, and the vibration amplitudes of mass m1
decreased very little. When the TMD is installed on the mass m3, the vibration amplitude
of massm3 significantly reduced, and the vibration amplitudes of massesm1, m2 decreased
very little.
4. CONCLUSION
In this paper, the sequential quadratic programming (SQP) method is used to cal-
culating parameter optimization of the tuned mass damper (TMD) for three-degree-of-
freedom vibration systems. The following concluding remarks have been reached:
- If the TMD is attached to the vibration source (excited force or kinematical ex-
citement), the effect of vibration reduction will be achieved globally.
- If the TMD is attached to the place far away from the vibration source, the effect
of vibration reduction will be achieved in the upper masses from the position of TMD.
224 Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan
- The SQP method can be used in solving complex constrained optimization prob-
lems for multibody systems.
ACKNOWLEDGEMENT
This paper was completed with the financial support by The Vietnam National
Foundation for Science and Technology Development (NAFOSTED).
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Received February 22, 2012
VIETNAM ACADEMY OF SCIENCE AND TECHNOLOGY
VIETNAM JOURNAL OF MECHANICS VOLUME 35, N. 3, 2013
CONTENTS
Pages
1. N. T. Khiem, L. K. Toan, N. T. L. Khue, Change in mode shape nodes of
multiple cracked bar: I. The theoretical study. 175
2. Nguyen Viet Khoa, Monitoring a sudden crack of beam-like bridge during
earthquake excitation. 189
3. Nguyen Trung Kien, Nguyen Van Luat, Pham Duc Chinh, Estimating
effective conductivity of unidirectional transversely isotropic composites. 203
4. Nguyen Van Khang, Trieu Quoc Loc, Nguyen Anh Tuan, Parameter
optimization of tuned mass damper for three-degree-of-freedom vibration
systems. 215
5. Tran Vinh Loc, Thai Hoang Chien, Nguyen Xuan Hung, On two-field nurbs-
based isogeometric formulation for incompressible media problems. 225
6. Tat Thang Nguyen, Hiroshige Kikura, Ngoc Hai Duong, Hideki Murakawa,
Nobuyoshi Tsuzuki, Measurements of single-phase and two-phase flows in
a vertical pipe using ultrasonic pulse Doppler method and ultrasonic time-
domain cross-correlation method. 239
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