Fuzzy Active Disturbance Rejection Control for Electro-Mechanical Actuator Based on Feedback Linearization

As an actuation mechanism for achieving precision attitude control in aircraft, the electromechanical actuator (EMA) plays a critical role in ensuring flight safety and stability. However, the EMA is subject to unmeasurable unknown disturbances that act through mismatched channels relative to the system’s control input. To address this, this paper employs feedback linearization to transform the existing model. The transformed model effectively recasts the unknown disturbance into the same channel as the control input, thereby enabling active disturbance rejection via control law design. Furthermore, to overcome the challenge of immeasurable disturbances, an extended state observer (ESO) is designed to estimate the unknown disturbance; the estimated value is then directly utilized in the control law synthesis. Subsequently, a fuzzy logic system (FLS) is developed to perform real-time online adaptation and optimization of the controller parameters. Finally, extensive simulation results are provided to validate the effectiveness of the proposed algorithm.

Authors

Institutions

Publication Details

Journal
Actuators
Published
2025-12-31
DOI
https://doi.org/10.3390/act15010018
Citations
1
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fuzzy Active Disturbance Rejection Control for Electro-Mechanical Actuator Based on Feedback Linearization

H. Sun, Jiang Ju, Xi Xiao
1 citations
Actuators
Adaptive Control of Nonlinear Systems
1.21
article

Fuzzy Active Disturbance Rejection Control for Electro-Mechanical Actuator Based on Feedback Linearization

H. Sun, Jiang Ju, Xi Xiao
article en
1 citations

Abstract

As an actuation mechanism for achieving precision attitude control in aircraft, the electromechanical actuator (EMA) plays a critical role in ensuring flight safety and stability. However, the EMA is subject to unmeasurable unknown disturbances that act through mismatched channels relative to the system’s control input. To address this, this paper employs feedback linearization to transform the existing model. The transformed model effectively recasts the unknown disturbance into the same channel as the control input, thereby enabling active disturbance rejection via control law design. Furthermore, to overcome the challenge of immeasurable disturbances, an extended state observer (ESO) is designed to estimate the unknown disturbance; the estimated value is then directly utilized in the control law synthesis. Subsequently, a fuzzy logic system (FLS) is developed to perform real-time online adaptation and optimization of the controller parameters. Finally, extensive simulation results are provided to validate the effectiveness of the proposed algorithm.

ActuatorsVol. 15(1)
Shenyang Aerospace University (CN), Guizhou Electromechanical Research and Design Institute (CN), Nanjing University of Aeronautics and Astronautics (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 14%
Adaptive Control of Nonlinear Systems
1.21
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.