Data-based Stabilization of Unknown Discrete-time 2-D Roesser Systems

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

Authors

Institutions

Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icmlc63072.2024.10935104
Primary Topic
Advanced Control and Stabilization in Aerospace Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data-based Stabilization of Unknown Discrete-time 2-D Roesser Systems

Runmin Yang, Yanzheng Zhu, Renjie Ma, Rongni Yang et al.
Advanced Control and Stabilization in Aerospace Systems
article

Data-based Stabilization of Unknown Discrete-time 2-D Roesser Systems

Runmin Yang, Yanzheng Zhu, Renjie Ma, Rongni Yang, Peng Shi
article en

Abstract

This paper studies the stabilization problem of discrete-time two-dimensional (2-D) systems represented by Roesser based on available data. First of all, based on the pre-collected input-state data, the original system is transformed into a data-based form. Then a set is established to represent all systems capable of generating the given data, thereby indirectly stabilizing the original system by stabilizing all systems within this set. Next, by utilizing the S-procedure, sufficient conditions are established for the resultant closed-loop systems that incorporate a state feedback controller based on collected data. Finally, an example is given to demonstrate the effectiveness of the proposed approach.

Shandong University (CN), Harbin Institute of Technology (CN), State Key Laboratory of Robotics and Systems (CN), The University of Adelaide (AU), Shandong University of Science and Technology (CN)
National Natural Science Foundation of China, Australian Research Council
Openalex Percentile: Top 53%
Advanced Control and Stabilization in Aerospace Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.