Fixed-Time Nonsingular based Sliding Mode Lateral Control for Autonomous Vehicle

This paper presents a fixed-time nonsingular sliding mode control (FTNSMC) for lateral path tracking under external disturbances. Using a quintic equation to define the desired trajectory, the proposed control ensures that the tracking error converges to zero within a fixed and predefined time, regardless of the initial conditions, and achieves this without chattering. The Teaching-Learning-Based Optimization (TLBO) algorithm is employed to tune the control gains, enhancing the overall performance of the controller. System stability is rigorously proven using the Lyapunov approach. Two distinct initial positions, y<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1|t=0</inf> = 0.3 and y<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2|t=0</inf> = 0.4, were selected, and in both cases, the system achieved convergence within the same fixed time, T=1.51s, which is significantly lower than the calculated maximum allowable time, T<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</inf>≈ 9.5s, thereby demonstrating the robustness and effectiveness of the proposed method.

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Publication Details

Published
2025-05-15
DOI
https://doi.org/10.1109/iraset64571.2025.11008165
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
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0.00
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article

Fixed-Time Nonsingular based Sliding Mode Lateral Control for Autonomous Vehicle

Houcine Chafouk, El Mehdi Mellouli, Vidas Žuraulis, Salma Khatory
Vehicle Dynamics and Control Systems
article

Fixed-Time Nonsingular based Sliding Mode Lateral Control for Autonomous Vehicle

Houcine Chafouk, El Mehdi Mellouli, Vidas Žuraulis, Salma Khatory
article en

Abstract

This paper presents a fixed-time nonsingular sliding mode control (FTNSMC) for lateral path tracking under external disturbances. Using a quintic equation to define the desired trajectory, the proposed control ensures that the tracking error converges to zero within a fixed and predefined time, regardless of the initial conditions, and achieves this without chattering. The Teaching-Learning-Based Optimization (TLBO) algorithm is employed to tune the control gains, enhancing the overall performance of the controller. System stability is rigorously proven using the Lyapunov approach. Two distinct initial positions, y<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1|t=0</inf> = 0.3 and y<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2|t=0</inf> = 0.4, were selected, and in both cases, the system achieved convergence within the same fixed time, T=1.51s, which is significantly lower than the calculated maximum allowable time, T<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</inf>≈ 9.5s, thereby demonstrating the robustness and effectiveness of the proposed method.

Vilnius Gediminas Technical University (LT), École Supérieure d'Ingénieurs en Génie Électrique (FR), National School of Architecture (MA), Université de Rouen Normandie (FR)
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Vehicle Dynamics and Control Systems
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