T–S Fuzzy Observer-Based Output Feedback Lateral Control of UGVs Using a Disturbance Observer

This paper introduces a novel observer-based fuzzy tracking controller that integrates disturbance estimation to improve state estimation and path tracking in the lateral control systems of Unmanned Ground Vehicles (UGVs). The design of the controller is based on linear matrix inequality (LMI) conditions derived from a Takagi–Sugeno fuzzy model and a relaxation technique that incorporates additional null terms. The state observer is developed to estimate both the vehicle’s state and external disturbances, such as road curvature. By incorporating the disturbance observer, the proposed approach effectively mitigates performance degradation caused by discrepancies between the system and observer dynamics. The simulation results, conducted in MATLAB and a commercial autonomous driving simulator, demonstrate that the proposed control method substantially enhances state estimation accuracy and improves the robustness of path tracking under varying conditions.

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Institutions

Publication Details

Journal
Drones
Published
2024-11-19
DOI
https://doi.org/10.3390/drones8110685
Citations
6
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
1.22

Funders

Controls
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article

T–S Fuzzy Observer-Based Output Feedback Lateral Control of UGVs Using a Disturbance Observer

Seunghoon Lee, Han Sol Kim, Sounghwan Hwang
6 citations
Drones
Vehicle Dynamics and Control Systems
1.22
article

T–S Fuzzy Observer-Based Output Feedback Lateral Control of UGVs Using a Disturbance Observer

Seunghoon Lee, Han Sol Kim, Sounghwan Hwang
article en
6 citations

Abstract

This paper introduces a novel observer-based fuzzy tracking controller that integrates disturbance estimation to improve state estimation and path tracking in the lateral control systems of Unmanned Ground Vehicles (UGVs). The design of the controller is based on linear matrix inequality (LMI) conditions derived from a Takagi–Sugeno fuzzy model and a relaxation technique that incorporates additional null terms. The state observer is developed to estimate both the vehicle’s state and external disturbances, such as road curvature. By incorporating the disturbance observer, the proposed approach effectively mitigates performance degradation caused by discrepancies between the system and observer dynamics. The simulation results, conducted in MATLAB and a commercial autonomous driving simulator, demonstrate that the proposed control method substantially enhances state estimation accuracy and improves the robustness of path tracking under varying conditions.

DronesVol. 8(11)
Purdue University West Lafayette (US), Dankook University (KR)
National Research Foundation of Korea
Openalex Percentile: Top 21%
Vehicle Dynamics and Control Systems
1.22
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