.png){kind=icon}
返回
Revisiting Model Reference Adaptive Control: Linear-Like Closed-Loop Behavior
.png){kind=icon}
PRE
AI
DOI：10.1109/TAC.2024.3462555.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this article, we examine the model reference adaptive control problem when the commonly used projection algorithm is utilized, subject to several common assumptions on the set of admissible parameters, in particular a compactness constraint as well as knowledge of the sign of the high-frequency gain. It is proven in the literature that for this setup, the closed-loop system is bounded-input bounded-state; since the closed-loop system is not linear time-invariant, this does not imply a bounded gain. Here, we prove a much crisper and detailed bound on the closed-loop behavior consisting of three terms: a decaying exponential on the initial condition, a linear-like convolution bound on the exogenous inputs, and a constant scaled by the square root of the constant in the denominator of the estimator update law; we also provide an upper bound on the two-norm of the tracking error. We then demonstrate that the same kind of bounds hold in the presence of a degree of unmodeled dynamics and plant parameter time-variation.
Keyword:
Adaptive control
Projection algorithms
Convolution
Stability analysis
Adaptation models
Vectors
Standards
Linear-like behavior
model reference adaptive control
projection algorithms
robustness
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
机构
引用论文
Adaptive sliding mode control for discrete-time multi-input multi-output systems.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏分享收藏
查看更多内容