An Enhanced Coupling Nonlinear Tracking Controller for Underactuated 3D Overhead Crane Systems

被引:27
作者
Zhang, Menghua [1 ]
Ma, Xin [1 ]
Rong, Xuewen [1 ]
Song, Rui [1 ]
Tian, Xincheng [1 ]
Li, Yibin [1 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Shandong, Peoples R China
关键词
Tracking control; Overhead crane systems; Underactuated systems; Lyapunov techniques; Barbalat's lemma; Coupling behavior; OUTPUT-FEEDBACK CONTROL; CONTAINER CRANES; PERFORMANCE; VIBRATION; DESIGN; MOTION;
D O I
10.1002/asjc.1683
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An enhanced coupling nonlinear tracking control method for an underactuated 3D overhead crane systems is set forth in the present paper. The proposed tracking controller guarantees a smooth start for the trolley and solves the problem of the payload swing angle amplitude increasing as the transferring distance gets longer for the regulation control methods. Different from existing tracking control methods, the presented control approach has an improved transient performance. More specifically, by taking the operation experience, mathematical analysis of the overhead crane system, physical constraints, and operational efficiency into consideration, we first select two desired trajectories for the trolley. Then, a new storage function is constructed by the introduction of two new composite signals, which increases the coupling behaviour between the trolley movement and payload swing. Next, a novel tracking control strategy is designed according to the derivation form of the aforementioned storage function. Lyapunov techniques and Barbalat's Lemma are used to demonstrate the stability of the closed-loop system without any approximation manipulations to the original nonlinear dynamics. Finally, some simulation and experiments are used to demonstrate the superior transient performance and strong robustness with respect to different cable lengths, payload masses, destinations, and external disturbances of the enhanced coupling nonlinear tracking control scheme.
引用
收藏
页码:1839 / 1854
页数:16
相关论文
共 50 条
[31]   Passivity-based adaptive trajectory control of an underactuated 3-DOF overhead crane [J].
Shen, Ping-Yen ;
Schatz, Julia ;
Caverly, Ryan James .
CONTROL ENGINEERING PRACTICE, 2021, 112
[32]   Trajectory Tracking Nonlinear Controller for Underactuated Underwater Vehicles Based on Velocity Transformation [J].
Herman, Przemyslaw .
JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2023, 11 (03)
[33]   Modeling and nonlinear energy-based anti-swing control of underactuated dual ship-mounted crane systems [J].
Hu, Die ;
Qian, Yuzhe ;
Fang, Yongchun ;
Chen, Yuzhu .
NONLINEAR DYNAMICS, 2021, 106 (01) :323-338
[34]   A Continuous Robust Antiswing Tracking Control Scheme for Underactuated Crane Systems With Experimental Verification [J].
Sun, Ning ;
Fang, Yongchun ;
Chen, He .
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2016, 138 (04)
[35]   3D trajectory tracking of underactuated non-minimum phase underwater vehicles [J].
Li, Ji-Hong .
AUTOMATICA, 2023, 155
[36]   Continuous Stabilization Controller for Nonlinear Systems With Two Piecewise Controllers and Its Application to Underactuated Ships [J].
Zhang, Zhong-Cai ;
Duan, Guang-Ren ;
Wu, Yu-Qiang .
IEEE TRANSACTIONS ON CYBERNETICS, 2025, 55 (04) :1594-1605
[37]   Backstepping Controller Applied to a Foldable Quadrotor for 3D Trajectory Tracking [J].
Derrouaoui, Saddam Hocine ;
Bouzid, Yasser ;
Guiatni, Mohamed ;
Kada, Halfaoui ;
Dib, Islam ;
Moudjari, Noureddine .
ICINCO: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 2020, :537-544
[38]   Design of Adaptive Time-Varying Sliding Mode Controller for Underactuated Overhead Crane Optimized via Improved Honey Badger Algorithm [J].
Wang, Tianlei ;
Zhou, Jing ;
Zhang, Qimei ;
Lin, Chengmin ;
Liang, Yanyang .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2023, 108 (03)
[39]   Second-order Sliding Mode Control of 3D Overhead Cranes [J].
Le Anh Tuan ;
Hoang Manh Cuong ;
Lee, Soon-Geul .
2013 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS), 2013,
[40]   Disturbance Compensation-Based Deep Reinforcement Learning Control Strategy for Underactuated Overhead Crane Systems: Design and Experiments [J].
Tan, Panlong ;
Liu, Junjie ;
Sun, Mingwei ;
Chen, Zengqiang .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2025, 26 (04) :4380-4390