Disturbance Estimation and Compensation in Exoskeleton Electric Drive Control with Neural Network

被引：0

作者：

Dinh Dang Truong ^{[1
]}

Belov, Mikhail P. ^{[1
]}

Pham Van Tuan ^{[2
]}

机构：

[1] St Petersburg Electrotech Univ LETI, Dept Robot & Ind Automat, St Petersburg, Russia

[2] Le Quy Don Tech Univ, Hanoi, Vietnam

来源：

PROCEEDINGS OF THE 2021 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (ELCONRUS) | 2021年

关键词：

Exoskeleton; electric drive; control system; disturbance estimation; disturbance compensation; neural network; SYSTEM-IDENTIFICATION; ADAPTIVE-CONTROL;

D O I：

10.1109/ElConRus51938.2021.9396641

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The article proposes a method to evaluate and compensate uncertain disturbance in exoskeleton electric drive control system. The mathematical model for exoskeleton electric drive system with taking into account the nonlinear components and the interaction force between exoskeleton and lower extremities is developed. The PD control combined with the RBF adaptive neural network is investigated with linear-quadratic regulator as the basic foundation of the feedback design to evaluate and compensate the unknown disturbances in control system. The PD ingredient is applied to stabilize the dominant model. The simulation results in Matlab/Simulink indicate that the proposed PD-linear quadratic regulator with adaptive neural network compensation is more efficiency in compared with the conventional PD-linear quadratic regulator.

引用

页码：821 / 825

页数：5

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