Adaptive dynamic programming-based controller with admittance adaptation for robot-environment interaction

被引：5
作者：
Zhan, Hong [1 ]
Huang, Dianye [1 ]
Chen, Zhaopeng [2 ]
Wang, Min [1 ]
Yang, Chenguang [3 ]
机构：
[1] South China Univ Technol, Key Lab Autonomous Syst & Networked Control, Minist Educ, Sch Automat Sci & Engn, Guangzhou, Peoples R China
[2] Univ Hamburg, Dept Informat, TAMS Grp, D-22527 Hamburg, Germany
[3] Univ West England, Bristol Robot Lab, Bristol BS16 1QY, Avon, England
来源：
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS | 2020年 / 17卷 / 03期
基金：
英国工程与自然科学研究理事会;
关键词：
Adaptive dynamic programming; admittance adaptation; neural network; optimal control; robot-environment interaction; TRACKING CONTROL; PID CONTROL; IMPEDANCE; MANIPULATORS; PARAMETERS; SYSTEMS;
D O I：
10.1177/1729881420924610
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
The problem of optimal tracking control for robot-environment interaction is studied in this article. The environment is regarded as a linear system and an admittance control with iterative linear quadratic regulator method is obtained to guarantee the compliant behaviour. Meanwhile, an adaptive dynamic programming-based controller is proposed. Under adaptive dynamic programming frame, the critic network is performed with radial basis function neural network to approximate the optimal cost, and the neural network weight updating law is incorporated with an additional stabilizing term to eliminate the requirement for the initial admissible control. The stability of the system is proved by Lyapunov theorem. The simulation results demonstrate the effectiveness of the proposed control scheme.
引用
收藏
页数：11
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