Model Predictive Control with Improved Current Loop Cascaded for Manipulator Systems

被引：0
|
作者：
Yuan, Zihang [1 ]
Tong, Chengde [1 ]
Liu, Faliang [1 ]
Yang, Shijie [1 ]
Wu, Dongliang [1 ]
Zheng, Ping [1 ]
机构：
[1] Harbin Inst Technol, Sch Elect Engn & Automat, Harbin, Heilongjiang, Peoples R China
来源：
2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019) | 2019年
基金：
中国国家自然科学基金; 中国博士后科学基金; 国家重点研发计划;
关键词：
model predictive control; improved current loop; decoupled state feedback; manipulator system;
D O I：
暂无
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：
In medical manipulator control system, torque-position control with high precision and fast dynamic response is required. In this paper, a control system that cascades model predictive control and improved PI control is proposed. Firstly, in order to balance the gravity of the robot arm, a gravity learning algorithm separating the fictional damping is designed. Then, the disturbance of current loop caused by speed variation is eliminated through the improved PI control with state feedback decoupling. The position control is optimized and the reference current trajectory is obtained through model predictive control. Torque-position control with gravity balance and high dynamic performance is realized through this control method.
引用
收藏
页码：1 / 6
页数：6
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