Output-Feedback Stabilization in Prescribed-Time of a Class of Reaction-Diffusion PDEs With Boundary Input Delay

Time-varying prescribed-time (PT) controllers use growing gains not only to achieve convergence in desired time but to reduce state peaking during stabilization and to also reduce the control effort by distributing it more evenly over the time interval of convergence. In this article, we consider a 1-D reaction-diffusion system with boundary input delay and propose a general method for studying the problem of PT boundary stabilization. To achieve this objective, we first reformulate the system as a PDE-PDE cascade system (i.e., a cascade of a linear transport partial differential equation (PDE) with a linear reaction-diffusion PDE), where the transport equation represents the effect of the input delay. We then apply a time-varying infinite-dimensional backstepping transformation to convert the cascade system into a prescribed-time stable (in short PTS) target system. The stability analysis is conducted on the target system, and the desired stability property is transferred back to the closed-loop system using the inverse transformation. The effectiveness of the proposed approach is demonstrated through numerical simulations.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-01-27
DOI
https://doi.org/10.1109/tac.2025.3535189
Citations
8
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
Field-Weighted Citation Impact
11.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Output-Feedback Stabilization in Prescribed-Time of a Class of Reaction-Diffusion PDEs With Boundary Input Delay

Miroslav Krstić, Salim Zekraoui, Wilfrid Perruquetti, Nicolás Espitia
8 citations
IEEE Transactions on Automatic Control
Nonlinear Dynamics and Pattern Formation
11.90
article

Output-Feedback Stabilization in Prescribed-Time of a Class of Reaction-Diffusion PDEs With Boundary Input Delay

Miroslav Krstić, Salim Zekraoui, Wilfrid Perruquetti, Nicolás Espitia
article en
8 citations

Abstract

Time-varying prescribed-time (PT) controllers use growing gains not only to achieve convergence in desired time but to reduce state peaking during stabilization and to also reduce the control effort by distributing it more evenly over the time interval of convergence. In this article, we consider a 1-D reaction-diffusion system with boundary input delay and propose a general method for studying the problem of PT boundary stabilization. To achieve this objective, we first reformulate the system as a PDE-PDE cascade system (i.e., a cascade of a linear transport partial differential equation (PDE) with a linear reaction-diffusion PDE), where the transport equation represents the effect of the input delay. We then apply a time-varying infinite-dimensional backstepping transformation to convert the cascade system into a prescribed-time stable (in short PTS) target system. The stability analysis is conducted on the target system, and the desired stability property is transferred back to the closed-loop system using the inverse transformation. The effectiveness of the proposed approach is demonstrated through numerical simulations.

IEEE Transactions on Automatic ControlVol. 70(8)
Université Claude Bernard Lyon 1 (FR), Centre National de la Recherche Scientifique (FR), Université de Lille (FR), University of California San Diego (US), Centre de Recherche en Informatique (FR), Université Bourgogne Franche-Comté (FR), Laboratoire d'Automatique, de Génie des Procédés et de Génie Pharmaceutique (FR), École Centrale de Lille (FR)
Openalex Percentile: Top 2%
Nonlinear Dynamics and Pattern Formation
11.90
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.