.png){kind=icon}
返回
Forward-looking persistent excitation in model predictive control
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2021.110033.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work deals with the problem of integrating persistence of excitation into nonlinear constrained model predictive control to estimate uncertain parameters while guaranteeing a stable closed loop. We propose an adaptive tracking model predictive control and conditions which guarantee persistent excitation and uniformly bounded closed loop signals of nonlinear systems, despite bounded noise and parameter uncertainty. This is achieved by actively designing persistence of excitation through the computation of a reference trajectory around some nominal stationary point depending on the parameter estimate, opening up the opportunity of balancing excitation against other requirements. Appealing to the Total Stability Theorem, the results are local and solution evolves in a non-infinitesimal ball in state and estimated parameter. (C) 2021 Elsevier Ltd. All rights reserved.
Keyword:
Adaptive control
Recursive least squares
Closed-loop identification
Model predictive control
Persistence of excitation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
机构
引用论文
.png){kind=icon}
Influence of the stem effect on radioluminescence signals from optical fibre Al2O3:C dosemeters
PREAI
分享收藏Nonlinear Reference Tracking: An Economic Model Predictive Control Perspective非线性参考跟踪: 经济模型预测控制视角
PREAI
分享收藏
查看更多内容