Adaptive Neural Control of Strict-feedback Systems with Predefined Constraints

被引：0

作者：

Gao, Fei ^{[1
]}

Zhang, Weiguang ^{[1
]}

Weng, Zhi ^{[1
]}

机构：

[1] Inner Mongolia Univ, Sch Elect Informat Engn, Hohhot 010021, Peoples R China

来源：

2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年

关键词：

Output constraint; nonlinear mapping; adaptive neural control; strict-feedback systems; NONLINEAR-SYSTEMS;

D O I：

10.1109/CCDC58219.2023.10326812

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, a novel nonlinear mapping is proposed to achieve the output constraints, which transforms constrained tracking errors into equivalent unconstrained ones. Further, adaptive neural network (NN) control of strict-feedback systems is investigated based on the above nonlinear mapping. The control method proposed in the paper ensures that all the signals are bounded, output constraints are never violated and asymptotic tracking performance is achieved. Finally, a numerical example is provided to verify the proposed scheme.

引用

页码：1056 / 1061

页数：6

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