Application of Improved Sliding Mode and Artificial Neural Networks in Robot Control

被引:0
|
作者
Pham, Duc-Anh [1 ]
Ahn, Jong-Kap [2 ]
Han, Seung-Hun [1 ]
机构
[1] Gyeongsang Natl Univ, Dept Mech Syst Engn, Tongyeong 53064, South Korea
[2] Gyeongsang Natl Univ, Training Ship Operat Ctr, Tongyeong 53064, South Korea
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 12期
关键词
sliding mode control; mobile robot; improved sliding surface; artificial neural network; MATLAB/Simulink;
D O I
10.3390/app14125304
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Mobile robots are autonomous devices capable of self-motion, and are utilized in applications ranging from surveillance and logistics to healthcare services and planetary exploration. Precise trajectory tracking is a crucial component in robotic applications. This study introduces the use of improved sliding surfaces and artificial neural networks in controlling mobile robots. An enhanced sliding surface, combined with exponential and hyperbolic tangent approach laws, is employed to mitigate chattering phenomena in sliding mode control. Nonlinear components of the sliding control law are estimated using artificial neural networks. The weights of the neural networks are updated online using a gradient descent algorithm. The stability of the system is demonstrated using Lyapunov theory. Simulation results in MATLAB/Simulink R2024a validate the effectiveness of the proposed method, with rise times of 0.071 s, an overshoot of 0.004%, and steady-state errors approaching zero meters. Settling times were 0.0978 s for the x-axis and 0.0902 s for the y-axis, and chattering exhibited low amplitude and frequency.
引用
收藏
页数:16
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