Abstract

The closed-loop control methods of bridge crane systems adopt the real-time signal feedback to improve the performance of the systems. The energy-based closed-loop control method of bridge crane systems can be used to design the controller by constructing the energy function of the system, which avoids the direct analysis of the complex motion state of the systems and has the clear physical significance. However, the conventional energy-based control methods have some problems, including slow response, poor performance of eliminating pendulum, and less parameters reflected by the control law. A novel load energy coupling-based underactuated control method for bridge cranes is proposed. The relationship between the energy of the bridge crane system and the energy of the load system is analyzed with the dynamic model of the two-dimensional bridge crane. The coupling function based on the load displacement and swing angle is constructed. The driving force of the system is obtained by Lyapunov method, and the control law is designed. The boundedness and convergence of the closed-loop control system are explained by the principle of LaSalle invariance. With the comparison experiments and results analysis, it is shown that the proposed method can obtain the better performance of eliminating swing and realize the accurate positioning of the trolley. It also reflects that this proposed method effectively reduces the dependence on model parameters and simplifies the control law.

References

1.
Alghanim
,
K.
,
Mohammed
,
A.
, and
Andani
,
M. T.
,
2019
, “
An Input Shaping Control Scheme With Application on Overhead Cranes
,”
Int. J. Nonlinear Sci. Numer. Simul.
,
20
(
5
), pp.
561
573
.10.1515/ijnsns-2018-0152
2.
Miao
,
Y.
,
Xu
,
F.
,
Hu
,
Y.
,
An
,
J.
, and
Zhang
,
M.
,
2019
, “
Anti-Swing Control of the Over Head Crane System Based on the Harmony Search Radial Basis Function Neural Network Algorithm
,”
Adv. Mech. Eng.
,
11
(
3
), pp.
1
10
.10.1177/1687814019834458
3.
Jui
,
J. J.
, and
Ahmad
,
M. A.
,
2021
, “
A Novel Hybridization of Average Multi-Verse Optimizer and Sine Cosine Algorithm for Identification of Continuous-Time Hammerstein Systems
,”
Appl. Math. Modell.
,
95
(
7
), pp.
339
360
.10.1016/j.apm.2021.01.023
4.
Ho
,
D. T.
,
Naoki
,
U.
, and
Kazuhiko
,
T.
,
2021
, “
Resonance-Based Tossing Control for Bulk Materials Transportation of an Overhead Crane
,”
IEEE Trans. Ind. Electron.
,
68
(
1
), pp.
609
621
.10.1109/TIE.2019.2962417
5.
Feng
,
K.
,
Ji
,
J. C.
,
Ni
,
Q.
, and
Beer
,
M.
,
2023
, “
A Review of Vibration-Based Gear Wear Monitoring and Prediction Techniques
,”
Mech. Syst. Signal Process.
,
182
(
1
), p.
109605
.10.1016/j.ymssp.2022.109605
6.
Sun
,
N.
,
Fang
,
Y.
,
Chen
,
H.
, and
Lu
,
B.
,
2017
, “
Amplitude-Saturated Nonlinear Output Feedback Antiswing Control for Underactuated Cranes With Double Pendulum Cargo Dynamics
,”
IEEE Trans. Ind. Electron.
,
64
(
3
), pp.
2135
2146
.10.1109/TIE.2016.2623258
7.
Sun
,
N.
,
Zhang
,
J.
,
Xin
,
X.
,
Yang
,
T.
, and
Fang
,
Y.
,
2019
, “
Nonlinear Output Feedback Control of Flexible Rope Crane Systems With State Constraints
,”
IEEE Access
,
7
(
9
), pp.
136193
136202
.10.1109/ACCESS.2019.2942054
8.
Wu
,
X.
, and
He
,
X.
,
2017
, “
Nonlinear Energy-Based Regulation Control of Three Dimensional Overhead Cranes
,”
IEEE Trans. Autom. Sci. Eng.
,
14
(
2
), pp.
1297
1308
.10.1109/TASE.2016.2542105
9.
Wu
,
X.
,
Zhao
,
Y.
, and
Xu
,
K.
,
2021
, “
Nonlinear Disturbance Observer Based Sliding Mode Control for a Benchmark System With Uncertain Disturbances
,”
ISA Trans.
,
110
(
4
), pp.
63
70
.10.1016/j.isatra.2020.10.032
10.
Tuan
,
L. A.
,
Cuong
,
H. M.
,
Van Trieu
,
P.
,
Nho
,
L. C.
,
Thuan
,
V. D.
, and
Le
,
V. A.
,
2018
, “
Adaptive Neural Network Sliding Mode Control of Shipboard Container Cranes Considering Actuator Backlash
,”
Mech. Syst. Signal Process.
,
112
(
11
), pp.
233
250
.10.1016/j.ymssp.2018.04.030
11.
Zhang
,
M.
,
Ma
,
X.
,
Rong
,
X.
,
Song
,
R.
,
Tian
,
X.
, and
Li
,
Y.
,
2018
, “
A Novel Energy Coupling-Based Control Method for Double-Pendulum Overhead Cranes With Initial Control Force Constraint
,”
Adv. Mech. Eng.
,
10
(
1
), pp.
1
13
.10.1177/1687814017752213
12.
Miao
,
X.
,
Zhao
,
B.
,
Wang
,
L.
, and
Ouyang
,
H.
,
2022
, “
Trolley Regulation and Swing Reduction of Underactuated Double-Pendulum Overhead Cranes Using Fuzzy Adaptive Nonlinear Control
,”
Nonlinear Dyn.
,
109
(
2
), pp.
837
847
.10.1007/s11071-022-07465-9
13.
Wang
,
T.
,
Lin
,
C.
,
Li
,
R.
,
Qiu
,
J.
,
He
,
Y.
,
Zhou
,
Z.
, and
Qiu
,
G.
,
2023
, “
Nonlinear Enhanced Coupled Feedback Control for Bridge Crane With Uncertain Disturbances: Theoretical and Experimental Investigations
,”
Nonlinear Dyn.
,
111
(
20
), pp.
19021
19032
.10.1007/s11071-023-08881-1
14.
Wang
,
M.
, and
Liu
,
J.
,
2024
, “
Modeling and Vibration Suppression for Overhead Crane in Planar Space With Nonlinear Time-Varying Actuator Faults and Uncertain Control Directions
,”
Nonlinear Dyn.
,
112
(
21
), pp.
18869
18883
.10.1007/s11071-024-10063-6
15.
Qian
,
Y.
, and
Fang
,
Y.
,
2019
, “
Switching Logic-Based Nonlinear Feedback Control of Offshore Ship-Mounted Tower Cranes: A Disturbance Observer-Based Approach
,”
Ann. Am. Thorac. Soc.
,
16
(
3
), pp.
1125
1136
.10.1109/TASE.2018.2872621
16.
Feng
,
K.
,
Smith
,
W.
,
Borghesani
,
P.
,
Randall
,
R. B.
, and
Peng
,
Z.
,
2021
, “
Use of Cyclostationary Properties of Vibration Signals to Identify Gear Wear Mechanisms and Track Wear Evolution
,”
Mech. Syst. Signal Process.
,
150
(
3
), p.
107258
.10.1016/j.ymssp.2020.107258
17.
Miranda-Colorado, R., and Aguilar, L. T.,
2019
, “
A Family of Anti-Swing Motion Controllers for 2D Cranes With Load Hoisting/Lowering
,”
Mech. Syst. Signal Process.
,
133
(
11
), p.
106253
.10.1016/j.ymssp.2019.106253
18.
Wu
,
X.
,
Xu
,
K.
, and
He
,
X.
,
2020
, “
Disturbance-Observer-Based Nonlinear Control for Overhead Cranes Subject to Uncertain Disturbances
,”
Mech. Syst. Signal Process.
,
139
(
5
), p.
106631
.10.1016/j.ymssp.2020.106631
19.
Tho
,
H. D.
,
Kaneshige
,
A.
, and
Terashima
,
K.
,
2020
, “
Minimum-Time S-Curve Commands for Vibration-Free Transportation of an Overhead Crane With Actuator Limits
,”
Control Eng. Pract.
,
98
(
11
), p.
104390
.10.1016/j.conengprac.2020.104390
20.
Ouyang
,
H.
,
Zhao
,
B.
, and
Zhang
,
G.
,
2021
, “
Enhanced-Coupling Nonlinear Controller Design for Load Swing Suppression in Three-Dimensional Overhead Cranes With Double-Pendulum Effect
,”
ISA Trans.
,
115
(
9
), pp.
95
107
.10.1016/j.isatra.2021.01.009
21.
Yang
,
Y.
,
Huang
,
J.
,
Xu
,
W.
,
Zhao
,
W.
, and
Yuan
,
H.
,
2022
, “
An Improved Method for Swing Measurement Based on Monocular Vision to the Payload of Overhead Crane
,”
Trans. Inst. Meas. Control
,
44
(
1
), pp.
50
59
.10.1177/0142331220921318
22.
Zhang
,
H.
,
Zhao
,
C.
, and
Ding
,
J.
,
2022
, “
Online Reinforcement Learning With Passivity-Based Stabilizing Term for Real Time Overhead Crane Control Without Knowledge of the System Model
,”
Control Eng. Pract.
,
127
(
10
), p.
105302
.10.1016/j.conengprac.2022.105302
23.
Kim
,
G. H.
,
Yoon
,
M.
,
Jeon
,
J. Y.
, and
Hong
,
K. S.
,
2022
, “
Data-Driven Modeling and Adaptive Predictive Anti-Swing Control of Overhead Cranes
,”
Int. J. Control, Autom. Syst.
,
20
(
8
), pp.
2712
2723
.10.1007/s12555-022-0025-8
24.
Lin
,
H.
, and
Lou
,
X.
,
2023
, “
Data-Driven Active Learning Control for Bridge Cranes
,”
Math. Comput. Appl.
,
28
(
5
), p.
101
.10.3390/mca28050101
25.
Miao
,
X.
,
Yang
,
L.
, and
Ouyang
,
H.
,
2023
, “
Artificial-Neural-Network-Based Optimal Smoother Design for Oscillation Suppression Control of Underactuated Overhead Cranes With Distributed Mass Beams
,”
Mech. Syst. Signal Process.
,
200
(
10
), p.
110497
.10.1016/j.ymssp.2023.110497
26.
Raúl
,
V. S.
,
Roger
,
M. C.
,
Jesus
,
A. R. A.
, and
Luis
,
T. A.
,
2024
, “
Observer-Based Proportional-Retarded Controller for Payload Swing Attenuation of 2D-Crane Systems Including Load Hoisting-Lowering
,”
ISA Trans.
,
155
(
12
), pp.
472
488
.10.1016/j.isatra.2024.09.022
27.
Sun
,
N.
,
Fang
,
Y. C.
, and
Chen
,
H.
,
2015
, “
Antiswing Tracking Control for Underactuated Bridge Cranes
,”
Control Theory Appl.
,
32
(
3
), pp.
326
333
.10.7641/CTA.2015.31139
28.
Li
,
F.
,
Zhang
,
C.
, and
Sun
,
B.
,
2019
, “
A Minimum-Time Motion Online Planning Method for Underactuated Overhead Crane Systems
,”
IEEE Access
,
7
(
4
), pp.
54586
54594
.10.1109/ACCESS.2019.2912460
29.
Huang
,
J. S.
,
Wang
,
W.
, and
Zhou
,
J.
,
2022
, “
Adaptive Control Design for Underactuated Cranes With Guaranteed Transient Performance: Theoretical Design and Experimental Verification
,”
IEEE Trans. Ind. Electron.
,
69
(
3
), pp.
2822
2832
.10.1109/TIE.2021.3065835
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