Adaptive Fixed-Time Sliding Mode Tracking Control of Underactuated AUVs with Flexible Prescribed Performance

This paper proposes a fixed-time nonsingular terminal sliding mode control (FXTNTSMC) method for underactuated autonomous underwater vehicles (AUVs) under uncertain dynamics and flexible prescribed performance. To address the inherent limitation of conventional prescribed performance control (PPC), the rigid performance bounds that may induce system instability under large disturbances, a flexible PPC strategy is proposed. This approach incorporates a risk monitoring mechanism that proactively predicts the tendency of the tracking error to violate performance constraints and dynamically adjusts the performance boundaries, thereby preserving transient performance while circumventing controller singularity. Furthermore, a FXTNTSMC law is designed to guarantee the tracking error can achieve a bounded region within a fixed time independent of initial conditions. An improved adaptive radial basis function neural network is employed for online approximation of the lumped disturbance, which consists of both uncertain dynamics and unknown external disturbances. Finally, a simulation shows that the superiority of the FXTNTSMC scheme in terms of tracking accuracy and convergence rate.

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Publication Details

Journal
Intelligence & Control
Published
2026-06-30
DOI
https://doi.org/10.53941/ic.2026.100007
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Adaptive Fixed-Time Sliding Mode Tracking Control of Underactuated AUVs with Flexible Prescribed Performance

Gaofeng Fan, Yu Zhao, Shuanghe Yu
Intelligence & Control
Adaptive Control of Nonlinear Systems
article

Adaptive Fixed-Time Sliding Mode Tracking Control of Underactuated AUVs with Flexible Prescribed Performance

Gaofeng Fan, Yu Zhao, Shuanghe Yu
article en

Abstract

This paper proposes a fixed-time nonsingular terminal sliding mode control (FXTNTSMC) method for underactuated autonomous underwater vehicles (AUVs) under uncertain dynamics and flexible prescribed performance. To address the inherent limitation of conventional prescribed performance control (PPC), the rigid performance bounds that may induce system instability under large disturbances, a flexible PPC strategy is proposed. This approach incorporates a risk monitoring mechanism that proactively predicts the tendency of the tracking error to violate performance constraints and dynamically adjusts the performance boundaries, thereby preserving transient performance while circumventing controller singularity. Furthermore, a FXTNTSMC law is designed to guarantee the tracking error can achieve a bounded region within a fixed time independent of initial conditions. An improved adaptive radial basis function neural network is employed for online approximation of the lumped disturbance, which consists of both uncertain dynamics and unknown external disturbances. Finally, a simulation shows that the superiority of the FXTNTSMC scheme in terms of tracking accuracy and convergence rate.

Intelligence & ControlVol. 2(2)
Dalian Maritime University (CN)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 9%
Adaptive Control of Nonlinear Systems
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