Improved Recursive-gradient-based Model-free Adaptive Control Algorithm

被引：2
|
作者：
Li, Xiu-Ying [1 ]
Wang, Jian [1 ]
机构：
[1] Shanghai Inst Technol, Sch Elect & Elect Engn, Shanghai 201418, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2022年 / 20卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Convergence analysis; model-free adaptive control; recursive gradient; DATA-DRIVEN CONTROL; SYSTEMS;
D O I：
10.1007/s12555-021-0290-y
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, the improved recursive-gradient-based model-free adaptive control algorithm is investigated where a momentum term is added in the form of parameter's change at the previous moment. It is that not only the direction but also the amplitude of the gradient descent are considered, the convergence speed of the algorithm is accelerated and therefore the dynamic performance of the system is enhanced. By rigorous mathematical induction, the convergence of output tracking error and the BIBO stability of the closed-loop system are proved. Simulation results demonstrate the effectiveness and feasibility of the proposed algorithm.
引用
收藏
页码：3512 / 3523
页数：12
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