A variable-parameter-model-based feedforward compensation method for tracking control

被引：7
|
作者：
Zhang, Dailin [1 ]
Wang, Zining [2 ]
Tomizuka, Masayoshi [2 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
[2] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
来源：
IEEE-CAA JOURNAL OF AUTOMATICA SINICA | 2020年 / 7卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Disturbance observer; feedforward compensation; iterative learning control; parameter identification; system model; ITERATIVE LEARNING CONTROL; SYSTEMS;
D O I：
10.1109/JAS.2020.1003135
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parameter-model-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.
引用
收藏
页码：693 / 701
页数：9
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