Fuzzy disturbance observer-based fuzzy swing suppression control of a ‘mooring-heavy lift crane-cargo’ coupled system

Hongdu Wang , Wenying Yang , Xiaolong Yang , Junrong Wang , Chenchen Shi

Intelligent Marine Technology and Systems ›› 2024, Vol. 2 ›› Issue (1)

PDF
Intelligent Marine Technology and Systems ›› 2024, Vol. 2 ›› Issue (1) DOI: 10.1007/s44295-024-00035-2
Research Paper

Fuzzy disturbance observer-based fuzzy swing suppression control of a ‘mooring-heavy lift crane-cargo’ coupled system

Author information +
History +
PDF

Abstract

In this paper, an adaptive fuzzy disturbance observer (FDO)-based control is proposed for the swing suppression of the mooring-heavy lift crane (HLC)-cargo system in the presence of a wave disturbance. First, the dynamic model of the HLC system is determined by employing the Lagrangian method, and the wave force is modeled as an exosystem with unknown terms based on the Jonswap spectrum. Then, based on the HLC model and the wave force exosystem, an FDO is established to determine the wave disturbances, and a fuzzy approximator is developed to estimate the unknown terms. A novel disturbance estimation error observer is first developed to facilitate the parameter adaptive updating law. Subsequently, by augmenting the HLC system and disturbance estimation error system, an FDO-based fuzzy antiswing control method is proposed in terms of the linear matrix inequality technique to suppress the swing. The closed-loop system stability is examined by using the Lyapunov method. Finally, the effectiveness of the proposed method is validated by numerical simulation.

Keywords

Fuzzy disturbance observer (FDO) / Adaptive fuzzy control / Heavy lift crane (HLC) / Nonlinear exosystem / Fuzzy swing suppression control

Cite this article

Download citation ▾
Hongdu Wang, Wenying Yang, Xiaolong Yang, Junrong Wang, Chenchen Shi. Fuzzy disturbance observer-based fuzzy swing suppression control of a ‘mooring-heavy lift crane-cargo’ coupled system. Intelligent Marine Technology and Systems, 2024, 2(1): DOI:10.1007/s44295-024-00035-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Cha JH, Roh MI, Lee KY. Dynamic response simulation of a heavy cargo suspended by a floating crane based on multibody system dynamics. Ocean Eng, 2010, 37(14–15): 1273-1291,

[2]

Chen H, Fang YC, Sun N. A swing constraint guaranteed MPC algorithm for underactuated overhead cranes. IEEE-ASME Trans Mechatron, 2016, 21(5): 2543-2555,

[3]

Chilinski B, Mackojc A, Zalewski R, Mackojc K. Proposal of the 3-DOF model as an approach to modelling offshore lifting dynamics. Ocean Eng, 2020, 203: 10723,

[4]

Cummins W. The impulse response function and ship motions. Schiffstechnik, 1962, 9: 101-109

[5]

Diebel J. Representing attitude: euler angles, unit quaternions, and rotation vectors. Matrix, 2006, 58: 1-35

[6]

Dong LW, Wei XJ (2018) Disturbance observer-based disturbance attenuation control for a class of stochastic systems with nonlinear exosystem and white noises. In: Proceedings of the 30th Chinese Control and Decision Conference (2018 CCDC), Shenyang, pp 5399–5404

[7]

Du JF, Chang AT, Wang SQ, Sun MY, Wang JR, Li HJ. Multi-mode reliability analysis of mooring system of deep-water floating structures. Ocean Eng, 2019, 192: 106517,

[8]

Guo L, Chen WH. Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach. Int J Robust Nonlinear Control, 2005, 15(3): 109-125,

[9]

He XY, He W, Shi J, Sun CY. Boundary vibration control of variable length crane systems in two-dimensional space with output constraints. IEEE-ASME Trans Mechatron, 2017, 22(5): 1952-1962,

[10]

Idres MM, Youssef KS, Mook DT, Nayfeh AH. A nonlinear 8-DOF coupled crane-ship dynamic model. In: 44th AIAA/ASME/ASCE/AHS Structures, Structural Dynamics, and Materials Conference, 2012 Norfolk AIAA 2003-1855

[11]

Ku N, Ha S. Dynamic response analysis of heavy load lifting operation in shipyard using multi-cranes. Ocean Eng, 2014, 83: 63-75,

[12]

Le AT, Lee SG. 3D cooperative control of tower cranes using robust adaptive techniques. J Franklin Inst-Eng Appl Math, 2017, 354(18): 8333-8357,

[13]

Li Y, Lin M. Regular and irregular wave impacts on floating body. Ocean Eng, 2012, 42: 93-101,

[14]

Lu Y. Adaptive-fuzzy control compensation design for direct adaptive fuzzy control. IEEE Trans Fuzzy Syst, 2018, 26(6): 3222-3231,

[15]

Ma HX, Chen M, Feng G, Wu QX. Disturbance-observer-based adaptive fuzzy tracking control for unmanned autonomous helicopter with flight boundary constraints. IEEE Trans Fuzzy Syst, 2023, 31(1): 184-198,

[16]

Nikiforov VO. Adaptive non-linear tracking with complete compensation of unknown disturbances. Eur J Control, 1998, 4(2): 132-139,

[17]

Qi SB, Wang HD, Wu HN, Guo L. Composite antidisturbance control for nonlinear systems via nonlinear disturbance observer and dissipative control. Int J Robust Nonlinear Control, 2019, 29(12): 4056-4068,

[18]

Qian YZ, Fang YC (2016) Dynamics analysis of an offshore ship-mounted crane subject to sea wave disturbances. In: Proceedings of the 2016 12th World Congress on Intelligent Control and Automation (WCICA), Guilin, 1251–1256

[19]

Qiu JB, Wang T, Sun KK, Rudas IJ, Gao HJ. Disturbance observer-based adaptive fuzzy control for strict-feedback nonlinear systems with finite-time prescribed performance. IEEE Trans Fuzzy Syst, 2022, 30(4): 1175-1184,

[20]

Smoczek J, Szpytko J. Particle swarm optimization-based multivariable generalized predictive control for an overhead crane. IEEE-ASME Trans Mechatron, 2017, 22(1): 258-268,

[21]

Sun W, Su SF, Wu YQ, Xia JW, Nguyen VT. Adaptive fuzzy control with high-order barrier Lyapunov functions for high-order uncertain nonlinear systems with full-state constraints. IEEE Trans Cybern, 2020, 50(8): 3424-3432,

[22]

Wang HD, Zhai YX, Shah UH, Karkoub M, Li M. Adaptive fuzzy control of underwater vehicle manipulator system with dead-zone band input nonlinearities via fuzzy performance and disturbance observers. Ocean Eng, 2023, 277,

[23]

Wang JR, He CL, Wang DZ, He K, He ZY, Zhang M, et al.. Investigation of second-order low-frequency wave forces approximations for moored floating structures. Ocean Eng, 2023, 282,

[24]

Wang JR, Shi CC, Wang HD, He CL. Dynamic analysis and swing suppression method of a ‘Mooring-HLC-Cargo’ coupled system. Ocean Eng, 2024, 295: 116840,

[25]

Wang LX. Stable adaptive fuzzy control of nonlinear systems. IEEE Trans Fuzzy Syst, 1993, 1(2): 146-155,

[26]

Wang XB, Li SY, Yu Y, Zhang J, Liu ZJ. Collaborative matching design method of lifting trajectory and ballast water allocation for revolving floating cranes with experimental validation. Ocean Eng, 2024, 296: 117033,

[27]

Wei XJ, Dong LW, Zhang HF, Han J, Hu X. Composite anti-disturbance control for stochastic systems with multiple heterogeneous disturbances and input saturation. ISA Trans, 2020, 100: 436-445,

[28]

Wei XJ, Guo L. Composite disturbance-observer-based control and H∞ control for complex continuous models. Int J Robust Nonlinear Control, 2010, 20(1): 106-118,

[29]

Wu HN, Liu ZY, Guo L. Robust L∞-gain fuzzy disturbance observer-based control design with adaptive bounding for a hypersonic aircraft. IEEE Trans Fuzzy Syst, 2014, 22(8): 1401-1412,

[30]

Yang T, Sun N, Chen H, Fang YC. Neural network-based adaptive antiswing control of an underactuated ship-mounted crane with roll motions and input dead zones. IEEE Trans Neural Netw Learn Syst, 2019, 31(3): 901-914,

[31]

Yao XM, Guo L. Composite anti-disturbance control for Markovian jump nonlinear systems via disturbance observer. Automatica, 2013, 49(8): 2538-2545,

[32]

Zanjani MS, Mobayen S. Anti-sway control of offshore crane on surface vessel using global sliding mode control. Int J Control, 2021, 95(8): 2267-2278,

[33]

Zhang FX, Hua J, Li YM. Indirect adaptive fuzzy control of SISO nonlinear systems with input-output nonlinear relationship. IEEE Trans Fuzzy Syst, 2018, 26(5): 2699-2708,

[34]

Zhang PY, Zhang SW, Wei YM, Le CH, Ding HY. Hydrodynamic characteristics of the crane vessel-three-bucket jacket foundation coupling hoisting system during the process of lowering. Ocean Eng, 2022, 250,

Funding

Key Technology Research and Development Program of Shandong Province(2023CXGC010408)

AI Summary AI Mindmap
PDF

199

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/