A historical perspective of adaptive control and learning

被引：75

作者：

Annaswamy, Anuradha M. ^{[1
]}

Fradkov, Alexander L. ^{[2
]}

机构：

[1] MIT, Dept Mech Engn, Cambridge, MA 02139 USA

[2] St Petersburg State Univ, Inst Problems Mech Engn, RAS, St Petersburg, Russia

来源：

ANNUAL REVIEWS IN CONTROL | 2021年 / 52卷

关键词：

Adaptive control; Learning; Parameter estimation; Stability and robustness; SLIDING-MODE CONTROL; SELF-TUNING REGULATORS; NONLINEAR-SYSTEMS; PARAMETER CONVERGENCE; NEURAL-CONTROL; RECURSIVE-IDENTIFICATION; LYAPUNOV FUNCTIONS; UNCERTAIN SYSTEMS; FEEDBACK; PLANTS;

D O I：

10.1016/j.arcontrol.2021.10.014

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article provides a historical perspective of the field of adaptive control over the past seven decades and its intersection with learning. A chronology of key events over this large time-span, problem statements that the field has focused on, and key solutions are presented. Fundamental results related to stability and robustness of adaptive systems and learning of unknown parameters are sketched. A brief description of various applications of adaptive control reported over this period is included.

引用

页码：18 / 41

页数：24

共 293 条

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