@inproceedings{1b49b17c52644f8ab2198a903c2947f9,
title = "Low-Dimensional-Agent-Model-Based Nonlinear MPC for Flexible Vibration Suppression",
abstract = "In this paper, a nonlinear model predictive control strategy is proposed based on a low-dimensional agent model to suppress the vibration of flexible beams governed by an Euler-Bernoulli beam equation. Dimensionality reduction is achieved for the high-dimensional vibration data via a deep autoencoder, effectively mapping the high-dimensional spatiotemporal data into a compact temporal domain. By the sparse identification of nonlinear dynamical systems with control algorithm, the agent model is identified from the reduced vibration data and used to derive optimal control actions based on the agent model outputs over a predefined time horizon. Numerical simulations demonstrate the proposed vibration control strategy's effectiveness.",
keywords = "Flexible beams, deep autoencoder, nonlinear model predictive control, sparse identification of nonlinear dynamics, vibration suppression",
author = "Cui, \{Jia Yu\} and Wu, \{Huai Ning\} and Wang, \{Jun Wei\}",
note = "Publisher Copyright: {\textcopyright} 2025 Technical Committee on Control Theory, Chinese Association of Automation.; 44th Chinese Control Conference, CCC 2025 ; Conference date: 28-07-2025 Through 30-07-2025",
year = "2025",
doi = "10.23919/CCC64809.2025.11179057",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "6747--6752",
editor = "Jian Sun and Hongpeng Yin",
booktitle = "Proceedings of the 44th Chinese Control Conference, CCC 2025",
address = "美国",
}