Data-Driven Adaptive Sliding Mode Control of Nonlinear Discrete-Time Systems With Prescribed Performance

被引:89
作者
Liu, Dong [1 ]
Yang, Guang-Hong [1 ,2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2019年 / 49卷 / 12期
基金
中国国家自然科学基金;
关键词
Model-free adaptive control; prescribed performance control (PPC); sliding mode control; TRACKING;
D O I
10.1109/TSMC.2017.2779564
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 paper deals with the issue of data-driven adaptive sliding mode control for a family of discrete-time non-linear processes with tracking error constraint. More specifically, a novel transformed error algorithm together with a new sliding mode control framework is investigated to ensure the tracking error converges to a predefined zone all the time. Moreover, the proposed controller can guarantee a convergence rate and steady-state behavior for the tracking error depending only on the input/output measurement data, which is more effective in the complex industrial processes. Simulations are given to validate the theoretical results.
引用
收藏
页码:2598 / 2604
页数:7
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