Abstract

Static response analysis of a dual crane system (DCS) is conducted using fuzzy parameters. The fuzzy static equilibrium equation is established and two fuzzy perturbation methods, including the compound function/fuzzy perturbation method (CFFPM) and modified compound function/fuzzy perturbation method (MCFFPM), are presented. The CFFPM uses the level-cut technique to transform the fuzzy static equilibrium equation into several interval equations with different cut levels. The interval Jacobian matrix, the first and second interval virtual work vectors, and the inverse of interval Jacobian matrix are approximated by the first-order Taylor series and Neumann series. The fuzzy static response field for every cut level is obtained by a synthesis of the compound function technique, the interval perturbation method, and the fuzzy algorithm. In the MCFFPM, the fuzzy static response field for every cut level is derived based on the surface rail generation method, the modified Sherman–Morrison–Woodbury (SMW) formula, and the fuzzy theory. Compared with the Monte Carlo method (MCM), numerical examples demonstrate that the MCFFPM has a better accuracy than the CFFPM and both of them bring a higher efficiency than the MCM, especially when it comes to effects of fuzzy parameters on uncertainty quantification (UQ) of the static response of the DCS.

References

1.
Merlet
,
J. P.
, and
Daney
,
D.
,
2010
, “
A Portable, Modular Parallel Wire Crane
for
Rescue Operations
,”
IEEE International Conference on Robotics and Automation
,
Alaska
,
May 3–8
, pp.
2834
2839
.
2.
Leban
,
F.
,
Gonzalez
,
J.
, and
Parker
,
G.
,
2015
, “
Inverse Kinematic Control of a Dual Crane System Experiencing Base Motion
,”
IEEE Trans. Control Syst. Technol.
,
23
(
1
), pp.
331
339
.
3.
Scalera
,
L.
,
Gallina
,
P.
,
Seriani
,
S.
, and
Gasparetto
,
A.
,
2018
, “
Cable-based Robotic Crane (CBRC): Design and Implementation of Overhead Traveling Cranes Based on Variable Radius Drums
,”
IEEE Trans. Robot.
,
34
(
2
), pp.
1
8
.
4.
Lu
,
B.
,
Fang
,
Y. C.
, and
Sun
,
N.
,
2018
, “
Modeling and Nonlinear Coordination Control for an Underactuated Dual Overhead Crane System
,”
Automatica
,
91
, pp.
244
255
.
5.
Hussein
,
H.
,
Santos
,
J. C.
,
Izard
,
J. B.
, and
Gouttefarde
,
M.
,
2021
, “
Smallest Maximum Cable Tension Determination for Cable-Driven Parallel Robots
,”
IEEE Trans. Robot.
,
99
, pp.
1
20
.
6.
Sun
,
N.
,
Fang
,
Y. C.
, and
Chen
,
H.
,
2015
, “
Adaptive Antiswing Control for Cranes in the Presence of Rail Length Constraints and Uncertainties
,”
Nonlinear Dyn.
,
81
(
1–2
), pp.
41
51
.
7.
Zi
,
B.
, and
Zhou
,
B.
,
2016
, “
A Modified Hybrid Uncertain Analysis Method for Dynamic Response Field of the LSOAAC With Random and Interval Parameters
,”
J. Sound Vib.
,
374
, pp.
111
137
.
8.
Eldred
,
M. S.
,
Swiler
,
L.
, and
Tang
,
G.
,
2011
, “
Mixed Aleatory-Epistemic Uncertainty Quantification With Stochastic Expansions and Optimization-Based Interval Estimation
,”
Reliab. Eng. Syst. Saf.
,
96
(
9
), pp.
1092
1113
.
9.
Elishakoff
,
I.
, and
Yao
,
J. T. P.
,
1984
, “
Probabilistic Methods in the Theory of Structures
,”
ASME J. Appl. Mech.
,
51
(
2
), pp.
451
452
.
10.
Moens
,
D.
, and
Hanss
,
M.
,
2011
, “
Non-Probabilistic Finite Element Analysis for Parametric Uncertainty Treatment in Applied Mechanics: Recent Advances
,”
Finite Elem. Anal. Des.
,
47
(
1
), pp.
4
16
.
11.
Neumaier
,
A.
,
1990
,
Interval Methods for Systems of Equations
,
Cambridge University Press
,
Cambridge, UK
.
12.
Qiu
,
Z. P.
, and
Elishakoff
,
I.
,
1998
, “
Anti-Optimization of Structures With Large Uncertain-But-Non-Random Parameters via Interval Analysis
,”
Comput. Methods Appl. Mech. Eng.
,
152
(
3–4
), pp.
361
372
.
13.
Sofi
,
A.
,
Muscolino
,
G.
, and
Elishakoff
,
I.
,
2015
, “
Natural Frequencies of Structures With Interval Parameters
,”
J. Sound Vib.
,
347
, pp.
79
95
.
14.
Xia
,
B. Z.
, and
Yu
,
D. J.
,
2012
, “
Modified Sub-Interval Perturbation Finite Element Method for 2D Acoustic Field Prediction With Large Uncertain-But-Bounded Parameters
,”
J. Sound Vib.
,
331
(
16
), pp.
3774
3790
.
15.
Shafer
,
G.
,
1976
,
A Mathematical Theory of Evidence
,
Princeton University Press
,
Princeton, NJ
.
16.
,
H.
,
Shangguan
,
W. B.
, and
Yu
,
D.
,
2016
, “
An Imprecise Probability Approach for Squeal Instability Analysis Based on Evidence Theory
,”
J. Sound Vib.
,
387
, pp.
96
113
.
17.
Yin
,
S. W.
,
Yu
,
D. J.
,
Yin
,
H.
, and
Xia
,
B. Z.
,
2017
, “
A New Evidence-Theory-Based Method for Response Analysis of Acoustic System With Epistemic Uncertainty by Using Jacobi Expansion
,”
Comput. Methods Appl. Mech. Eng.
,
322
, pp.
419
440
.
18.
Cao
,
L. X.
,
Liu
,
J.
,
Jiang
,
C.
,
Wu
,
Z. T.
, and
Zhang
,
Z.
,
2020
, “
Evidence-Based Structural Uncertainty Quantification by Dimension Reduction Decomposition and Marginal Interval Analysis
,”
ASME J. Mech. Des.
,
142
(
5
), p.
051701
.
19.
Ben-Haim
,
Y.
, and
Elishakoff
,
I.
,
1990
,
Convex Models of Uncertainty in Applied Mechanics
,
Elsevier Science
,
Amsterdam
.
20.
Xia
,
B. Z.
, and
Yu
,
D. J.
,
2014
, “
Response Analysis of Acoustic Field With Convex Parameters
,”
ASME J. Vib. Acoust.
,
136
(
4
), p.
041017
.
21.
Zadeh
,
L. A.
,
1965
, “
Fuzzy Sets
,”
Inf. Control
,
8
(
3
), pp.
338
353
.
22.
Rao
,
S. S.
, and
Sawyer
,
J. P.
,
1995
, “
A Fuzzy Element Approach for the Analysis of Imprecisely Defined System
,”
AIAA J.
,
33
(
12
), pp.
2364
2370
.
23.
Chen
,
L.
, and
Rao
,
S. S.
,
1997
, “
Fuzzy Finite-Element Approach for the Vibration Analysis of Imprecisely-Defined Systems
,”
Finite Elem. Anal. Des.
,
27
(
1
), pp.
69
83
.
24.
Massa
,
F.
,
Tison
,
T.
, and
Lallemand
,
B.
,
2006
, “
A Fuzzy Procedure for the Static Design of Imprecise Structures
,”
Comput. Methods Appl. Mech. Eng.
,
195
(
9–12
), pp.
925
941
.
25.
Wang
,
C.
, and
Qiu
,
Z. P.
,
2015
, “
Uncertain Temperature Field Prediction of Heat Conduction Problem With Fuzzy Parameters
,”
Int. J. Heat Mass Transfer
,
91
, pp.
725
733
.
26.
Balu
,
A. S.
, and
Rao
,
B. N.
,
2012
, “
High Dimensional Model Representation Based Formulations for Fuzzy Finite Element Analysis of Structures
,”
Finite Elem. Anal. Des.
,
50
, pp.
217
230
.
27.
Yin
,
H.
,
Yu
,
D. J.
,
Yin
,
S. W.
, and
Xia
,
B.
,
2016
, “
Fuzzy Interval Finite Element/Statistical Energy Analysis for Mid-Frequency Analysis of Built-up Systems With Mixed Fuzzy and Interval Parameters
,”
J. Sound Vib.
,
380
, pp.
192
212
.
28.
Wang
,
C.
, and
Qiu
,
Z. P.
,
2016
, “
Subinterval Perturbation Methods for Uncertain Temperature Field Prediction With Large Fuzzy Parameters
,”
Int. J. Therm. Sci.
,
100
, pp.
381
390
.
29.
Zhou
,
B.
,
Zi
,
B.
, and
Qian
,
S.
,
2017
, “
Dynamics-Based Nonsingular Interval Model and Luffing Angular Response Field Analysis of the DACS With Narrowly Bounded Uncertainty
,”
Nonlinear Dyn.
,
90
(
4
), pp.
2599
2626
.
30.
Zi
,
B.
,
Zhou
,
B.
,
Zhu
,
W. D.
, and
Wang
,
D. M.
,
2019
, “
Hybrid Function-Based Moment Method for Luffing Angular Response of Dual Automobile Crane System With Random and Interval Parameters
,”
ASME J. Comput. Nonlinear Dyn.
,
14
(
1
), p.
011003
.
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