Neural Network-Based Optimal Control of a Lower-limb Exoskeleton Robot

被引:0
作者
Huang, Pengbo [1 ]
Yuan, Wang [2 ]
Li, Qinjian [1 ]
Feng, Ying [3 ]
机构
[1] Univ Sci & Technol China, Dept Automat, Hefei, Peoples R China
[2] Univ Sci & Technol China, Inst Adv Technol, Hefei, Peoples R China
[3] South China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510641, Peoples R China
来源
2021 6TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2021) | 2021年
关键词
Lower-limb exoskeleton robot; optimal control; neural network; DESIGN;
D O I
10.1109/ICARM52023.2021.9536198
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, an optimal controller is designed and applied to the lower-limb exoskeleton robot, which could improve the robustness under nonlinear perturbations. In order to derive the optimal controller, we build the modeling of the exoskeleton robot to simplify the structure of the robot, and then we define a cost function, because the cost function is difficult to solve, so we adopt the function approximation method to approximate its optimal value, and the optimal control is obtained by solving the Hamiltonian equation. Finally, simulation studies are carried out. These simulation studies verify that the controller has a good performance even in the presence of disturbance.
引用
收藏
页码:154 / 159
页数:6
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