A Novel Zeroing Neural Network Control Scheme for Tracked Mobile Robot Based on an Extended State Observer

被引:0
|
作者
Cao, Yuxuan [1 ]
Pu, Jinyun [1 ]
机构
[1] Naval Univ Engn, Coll Power Engn, Wuhan 430033, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 01期
关键词
tracked mobile robot; extended state observer; fixed time; zeroing neural network; TIME CONVERGENCE; DESIGN;
D O I
10.3390/app14010303
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A novel zeroing neural network control scheme based on an extended state observer is proposed for the trajectory tracking of a tracked mobile robot which is subject to unknown external disturbances and uncertainties. To estimate unknown lumped disturbances and unmeasured velocities, a third-order fixed-time extended state observer is proposed, and the observation errors converge to zero in fixed time. Based on the estimated values, the zeroing neural network controller is designed for a tracked mobile robot to track an eight shape. The stability of the system is analyzed based on Lyapunov theory. Simulation results are illustrated to show the effectiveness of the proposed control scheme.
引用
收藏
页数:17
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