A Robust Neural Predictive Control Approach for Robotic Manipulators with Online Learning Ability

被引：0
|
作者：
Nguyen Hai Phong [1 ]
Dang Xuan Ba [1 ]
机构：
[1] HCMC Univ Technol & Educ HCMUTE, Dept Automatc Control, Ho Chi Minh City, Vietnam
来源：
2022 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS) | 2022年
关键词：
Robot Manipulators; Model Predictive Control; Neural Network; Robust Control; Intelligent Control; MODEL-ERROR MODEL;
D O I：
10.1109/ICCAIS56082.2022.9990358
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, we develop a new predictive controller for tracking control problems of robotic manipulators. Internal dynamics of the robotic model are first modeled using proper neural networks under support of an output feedback control signal. A new model predictive control signal is next derived to realize the control objective in a robust manner. Novel adaptation laws are then proposed to activate the network learning in an effective way. Effectiveness of the proposed controller has been validated throughout intensive simulation results on two degree of freedom robot.
引用
收藏
页码：482 / 486
页数：5
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