Adaptive Fuzzy Dynamic Surface Control with Sliding Mode Control for Enhanced Trajectory Tracking of Delta Robots

被引:0
作者
Dinh, Xuan-Minh [3 ]
Luong, Truong-Giang [2 ]
Le, Xuan-Hai [1 ]
Nguyen, Van-Tuan [3 ]
Kim, Dinh-Thai [1 ]
机构
[1] Vietnam Natl Univ Hanoi, Int Sch, Hanoi 100000, Vietnam
[2] Vietnam Natl Univ Hanoi, Univ Engn & Technol, Hanoi 100000, Vietnam
[3] Phenikaa Univ, Fac Mech Engn & Mechatron, Hanoi 100000, Vietnam
关键词
Dynamic surface control; Sliding mode control; Fuzzy logic; Delta robot; Trajectory tracking; Lyapunov stability; DESIGN;
D O I
10.1007/s40313-025-01180-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes an Adaptive Fuzzy Dynamic Surface Sliding Mode Control (AFDSC-SMC) method, specifically designed for precise trajectory tracking in a three-degree-of-freedom (3-DOF) Delta robot. By integrating Dynamic Surface Control (DSC) with Sliding Mode Control (SMC), the proposed approach effectively mitigates chattering, ensuring smooth control actions and enhanced tracking accuracy. An adaptive fuzzy logic mechanism is incorporated to dynamically adjust control parameters, thereby improving robustness against uncertainties and external disturbances. The stability of the closed-loop system is rigorously analyzed using Lyapunov theory, guaranteeing input-to-state stability (ISS). To validate the effectiveness of the proposed method, extensive simulations are conducted in MATLAB/Simulink across various trajectory scenarios. The performance of AFDSC-SMC is compared with that of traditional DSC and Backstepping Sliding Mode Control (BSP-SMC) under conditions involving disturbances and variations in model parameters. Simulation results demonstrate that AFDSC-SMC achieves stability within 0.15 s for three joints without overshooting. Furthermore, the proposed controller minimizes steady-state tracking errors to zero, delivering smooth control inputs within a range of +/- 15 Nm, outperforming conventional DSC and BSP-SMC. Quantitative visualizations further highlight that AFDSC-SMC significantly enhances trajectory tracking performance, providing precise end-effector positioning and robust operation in high-speed automation applications.
引用
收藏
页码:611 / 635
页数:25
相关论文
共 29 条
[21]   Adaptive Sliding-Mode Antisway Control of Uncertain Overhead Cranes With High-Speed Hoisting Motion [J].
Park, Mun-Soo ;
Chwa, Dongkyoung ;
Eom, Myunghwan .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (05) :1262-1271
[22]  
Santos JC, 2022, IEEE T ROBOT, V38, P2597, DOI [10.1109/TRO.2022.3152705, 10.1109/IECON49645.2022.9968541]
[23]  
Su TT, 2019, 2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019), P508, DOI 10.1109/SSCI44817.2019.9003125
[24]   Adaptive neural network hierarchical sliding mode control for six degrees of freedom overhead crane [J].
Thai Dinh Kim ;
Thien Nguyen ;
Dung Manh Do ;
Hai Xuan Le .
ASIAN JOURNAL OF CONTROL, 2023, 25 (04) :2736-2751
[25]  
Uzunovic T, 2013, 2013 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO), P497
[26]  
Van Khang N., 2015, J COMPUT SCI CYBERN, V31, P71, DOI [10.15625/1813-9663/31/1/5088, DOI 10.15625/1813-9663/31/1/5088]
[27]  
Yang WR, 2022, CHIN CONTR CONF, P750, DOI 10.23919/CCC55666.2022.9902280
[28]   Adaptive Control of a Linear Delta Robot Based on Backstepping Design [J].
Yang, Zhi-Xiang ;
Peng, Jing-Quan ;
Chen, Mei-Yung .
2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2018, :1138-1141
[29]   Trajectory Tracking of Delta Parallel Robot via Adaptive Backstepping Fractional-Order Non-Singular Sliding Mode Control [J].
Zhu, Dachang ;
He, Yonglong ;
Li, Fangyi .
MATHEMATICS, 2024, 12 (14)