先验与后验
有界函数
控制理论(社会学)
数学
理论(学习稳定性)
自适应控制
滑模控制
数学优化
国家(计算机科学)
计算机科学
控制(管理)
算法
人工智能
非线性系统
数学分析
认识论
机器学习
物理
量子力学
哲学
作者
S. Roy,Simone Baldi,Leonid Fridman
出处
期刊:Automatica
[Elsevier BV]
日期:2019-10-26
卷期号:111: 108650-108650
被引量:180
标识
DOI:10.1016/j.automatica.2019.108650
摘要
Adaptive Sliding Mode Control (ASMC) aims to adapt the switching gain in such a way to cope with possibly unknown uncertainty. In state-of-the-art ASMC methods, a priori boundedness of the uncertainty is crucial to ensure boundedness for the switching gain and uniformly ultimately boundedness. A priori bounded uncertainty might impose a priori bounds on the system state before obtaining closed-loop stability. A design removing this assumption is still missing in literature. A positive answer to this quest is given by this note where a novel ASMC methodology is proposed which does not require a priori bounded uncertainty. An illustrative example is presented to highlight the main features of the approach, after which a general class of Euler–Lagrange systems is taken as a case study to show the applicability of the proposed design.
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