Temporal Logic Disturbance Rejection Control of Nonlinear Systems Using Control Barrier Functions

The high level of autonomy within autonomous systems demands new control strategies to achieve more complex objectives while ensuring both safety and robustness, rather than relying solely on a given reference. To this end, this article addresses the problem of temporal logic disturbance rejection control (TLDRC) for a class of nonlinear systems subject to disturbances. Signal temporal logic (STL) specifications are introduced for the representation of complex tasks. A control barrier function (CBF), composed of a monotonic function characterizing the temporal behavior of the system and a predicate function, is constructed to encode the STL specifications. To guarantee robustness against disturbances, generalized proportional integral observers (GPIOs) are introduced for higher-accuracy disturbance estimation. It is shown that by fully exploiting the constructed CBF and the disturbance estimate, the developed TLDRC strategy is able to ensure the STL specifications and compensate undesirable effects caused by unknown disturbances, even if they are fast-time-varying. A numerical example is presented to illustrate the effectiveness of the proposed strategy.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Cybernetics
Published
2024-12-24
DOI
https://doi.org/10.1109/tcyb.2024.3515456
Citations
7
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
2.30

Funders

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

Temporal Logic Disturbance Rejection Control of Nonlinear Systems Using Control Barrier Functions

Chengqian Zhou, Jun Yang, Wen‐Hua Chen, Shihua Li
7 citations
IEEE Transactions on Cybernetics
Advanced Control Systems Optimization
2.30
article

Temporal Logic Disturbance Rejection Control of Nonlinear Systems Using Control Barrier Functions

Chengqian Zhou, Jun Yang, Wen‐Hua Chen, Shihua Li
article en
7 citations

Abstract

The high level of autonomy within autonomous systems demands new control strategies to achieve more complex objectives while ensuring both safety and robustness, rather than relying solely on a given reference. To this end, this article addresses the problem of temporal logic disturbance rejection control (TLDRC) for a class of nonlinear systems subject to disturbances. Signal temporal logic (STL) specifications are introduced for the representation of complex tasks. A control barrier function (CBF), composed of a monotonic function characterizing the temporal behavior of the system and a predicate function, is constructed to encode the STL specifications. To guarantee robustness against disturbances, generalized proportional integral observers (GPIOs) are introduced for higher-accuracy disturbance estimation. It is shown that by fully exploiting the constructed CBF and the disturbance estimate, the developed TLDRC strategy is able to ensure the STL specifications and compensate undesirable effects caused by unknown disturbances, even if they are fast-time-varying. A numerical example is presented to illustrate the effectiveness of the proposed strategy.

IEEE Transactions on CyberneticsVol. 55(3)
Loughborough University (GB), Southeast University (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 11%
Advanced Control Systems Optimization
2.30
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.

Temporal Logic Disturbance Rejection Control of Nonlinear Systems Using Control Barrier Functions — Chengqian Zhou, Jun Yang, et al. · IEEE Transactions on Cybernetics (2024) | TGRS Research Map | TGRS