Journal of System Simulation
Abstract
Abstract: Trajectory tracking is an important part of mobile robot control technology and possesses prospect. Highly nonlinear dynamic characteristics are the main obstacles of controller design. A SMC method based on LSTM and quasi-sliding mode is proposed. The kinematics model and dynamics model of the tracked vehicle are given, and the sliding mode control system is established based on the dynamics model. LSTM network based on deep learning method is designed to control and compensate the unknown interference items, reduce the influence of external interference, and reduce the tremor phenomenon by combining the advantages of LSTM network and quasi-sliding mode. The stability analysis of the control system is given. MATLAB/Simulink simulation experiments are carried out on different trajectories. Compared with the existing methods, the superiority is proven.
Recommended Citation
Liu, Dongyang; Zha, Wenwen; Tao, Liang; Zhu, Cheng; Gu, Lichuan; and Jiao, Jun
(2023)
"Trajectory Control of Crawler Robot Based on LSTM and SMC,"
Journal of System Simulation: Vol. 35:
Iss.
4, Article 6.
DOI: 10.16182/j.issn1004731x.joss.21-1248
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol35/iss4/6
First Page
747
Revised Date
2022-01-22
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-1248
Last Page
759
CLC
TP183
Recommended Citation
Dongyang Liu, Wenwen Zha, Liang Tao, Cheng Zhu, Lichuan Gu, Jun Jiao. Trajectory Control of Crawler Robot Based on LSTM and SMC[J]. Journal of System Simulation, 2023, 35(4): 747-759.
DOI
10.16182/j.issn1004731x.joss.21-1248
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