Model-Free Filter-Based Trajectory Tracking Controller for Two-Wheeled Vehicles Through Pole-Zero Cancellation Technique

Considering the nonlinear dynamics, this paper devises an advanced position trajectory tracking controller with a model-free filter for two-wheeled vehicle (TWV) applications. The proposed technique preserves a simple structure in the form of the proportional–integral (PI) controller involving the model-free filter and nonlinearly structured feedback gains, which make the following contributions: (a) the proposed filter smooths the position and yaw angle measurements according to the first-order convergence rate without any model information; and (b) the PI control with the nonlinearly structured feedback gains robustly stabilizes the position and yaw angle errors along the desired first-order system to accomplish the trajectory tracking mission, which is obtained by the pole-zero cancellation (PZC) in the presence of modeling errors. MATLAB/Simulink was used to emulate the resulting feedback system and validate the effectiveness of the proposed technique.

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Publication Details

Journal
Vehicles
Published
2024-11-11
DOI
https://doi.org/10.3390/vehicles6040093
Primary Topic
Control and Dynamics of Mobile Robots
Type
article
Field-Weighted Citation Impact
0.00
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article

Model-Free Filter-Based Trajectory Tracking Controller for Two-Wheeled Vehicles Through Pole-Zero Cancellation Technique

Seok‐Kyoon Kim, Kyung-Soo Kim, Yonghun Kim, Se H. Oh et al.
Vehicles
Control and Dynamics of Mobile Robots
article

Model-Free Filter-Based Trajectory Tracking Controller for Two-Wheeled Vehicles Through Pole-Zero Cancellation Technique

Seok‐Kyoon Kim, Kyung-Soo Kim, Yonghun Kim, Se H. Oh, Hosik Lee
article en

Abstract

Considering the nonlinear dynamics, this paper devises an advanced position trajectory tracking controller with a model-free filter for two-wheeled vehicle (TWV) applications. The proposed technique preserves a simple structure in the form of the proportional–integral (PI) controller involving the model-free filter and nonlinearly structured feedback gains, which make the following contributions: (a) the proposed filter smooths the position and yaw angle measurements according to the first-order convergence rate without any model information; and (b) the PI control with the nonlinearly structured feedback gains robustly stabilizes the position and yaw angle errors along the desired first-order system to accomplish the trajectory tracking mission, which is obtained by the pole-zero cancellation (PZC) in the presence of modeling errors. MATLAB/Simulink was used to emulate the resulting feedback system and validate the effectiveness of the proposed technique.

VehiclesVol. 6(4)
Hanbat National University (KR), Korea Advanced Institute of Science and Technology (KR), Chungnam National University (KR), Suwon Research Institute (KR)
Openalex Percentile: Top 76%
Control and Dynamics of Mobile Robots
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