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.
- Open Access
- Article
Adaptive Fixed-Time Sliding Mode Tracking Control of Underactuated AUVs with Flexible Prescribed Performance
- Gaofeng Fan,
- Ying Zhao *,
- Shuanghe Yu
Author Information
Received: 21 Apr 2026 | Revised: 14 Jun 2026 | Accepted: 17 Jun 2026 | Published: 30 Jun 2026
Abstract
Keywords
underactuated autonomous underwater vehicles | fixed-time nonsingular terminal sliding mode | flexible prescribed performance control
References
- 1.
Zhao, W.; Xia, Y.; Zhai, D.; et al. Event-Triggered Formation Control of Unknown Autonomous Underwater Vehicles Subject to Arbitrarily Large Time-Varying Communication Delays. IEEE Trans. Veh. Technol. 2025, 74, 3901–3912.
- 2.
Lin, C.; Zhang, Y.; Han, G.; et al. Multiple Autonomous Underwater Vehicles-Assisted Data Collection in 6G-Driven UnderwaterWireless Networks Based on Software-Defined MARL. IEEE Trans. Intell. Transp. Syst. 2025, 26, 17928–17939.
- 3.
Yu, L.; Qiao, L.; Shen, C. High-Speed Obstacle Avoidance of a Large-Scale Underactuated Autonomous Underwater Vehicle Under a Finite Field of View. IEEE Trans. Autom. Sci. Eng. 2025, 22, 1996–2005.
- 4.
Cao, Z.; Fan, H.; Hu, X.; et al. Complete Coverage Search for Multiple Autonomous Underwater Vehicles Based on Neuronal Activity Reassignment. IEEE Trans. Intell. Transp. Syst. 2025, 26, 9693–9710.
- 5.
Wang, M.; Juan, R.; Li, Z.; et al. Formation Control and Intention Compensating of AUVs Using Multi-Agent Reinforcement Learning and Predict Network. Ocean Eng. 2025, 342, 122854.
- 6.
Wang, J.; Li, T. Guest Editorial Special Issue on AI-Powered Planning and Control of Autonomous Marine Vehicles. IEEE Trans. Syst. Man Cybern. Syst. 2025, 55, 2–3.
- 7.
Xi, M.; Wen, J.; He, J.; et al. An Expert Experience-Enhanced Security Control Approach for AUVs of the Underwater Transportation Cyber-Physical Systems. IEEE Trans. Intell. Transp. Syst. 2025, 26, 14086–14098.
- 8.
Wang, J.; Cui, H.; Xu, H.; et al. Protocol-Based Dissipative Consensus Formation Control for Multi-AUVs with Transmission Delays. IEEE Trans. Veh. Technol. 2025,75, 7078–7090.
- 9.
Wang, Z.; Wen, J.; Xi, M.; et al. An Information-Interdependence Deep Reinforcement Learning Path Planning Scheme for AUV with Ocean Currents Utilization. IEEE Trans. Veh. Technol. 2026, 75, 3816–3828.
- 10.
Wang, X.; Xu, B.; Guo, Y. Minimum Error Entropy Robust Delay Filter for Multi-AUV Cooperative Localization. IEEE/ASME Trans. Mechatron. 2025, 30, 1567–1577.
- 11.
Ali, N.; Tawiah, I.; Zhang, W.; et al. Finite-Time Extended State Observer Based Nonsingular Fast Terminal Sliding Mode Control of Autonomous Underwater Vehicles. Ocean Eng. 2020, 218, 108179.
- 12.
Xia, G.; Zhang, Y.; Zhang, W.; et al. Robust Adaptive Super-Twisting Sliding Mode Formation Controller for Homing of Multi-Underactuated AUV Recovery System with Uncertainties. ISA Trans. 2022, 130, 136–151.
- 13.
Hou, Y.; Jin, X.; Qin, J. Adaptive RBFNN-Based Fixed-Time Event-Triggered Control of a Class of Disturbed Euler-Lagrange Systems with Actuator Faults. J. Franklin Inst. 2025, 362, 108116.
- 14.
Long, H.; Zhang, P.; Guo, T.; et al. Saturated Adaptive Fuzzy Fixed-Time Nonsingular Integral Terminal Sliding-Mode Control of AUVs. IEEE Trans. Cybern. 2025, 55, 1634–1647.
- 15.
Zhang, P.; He, X.; Yu, J. A Distributed Fixed-Time Neurodynamic Algorithm and Its Application in Multi-Autonomous Underwater Vehicle Collaborative Escorting. IEEE Trans. Netw. Sci. Eng. 2025, 12, 4140–4151.
- 16.
Li, X.; Qin, H.; Li, L.; et al. Fixed-Time Velocity-Free Safe Formation Control of AUVs with Actuator Saturation and Unknown Disturbances. Ocean Eng. 2023, 285, 115361.
- 17.
Su, B.; Wang, H.; Wang, Y. Dynamic Event-Triggered Formation Control for AUVs with Fixed-Time Integral Sliding Mode Disturbance Observer. Ocean Eng. 2021, 240, 109893.
- 18.
Li, J.; Du, J.; Li, Y.; et al. Distributed Robust Prescribed Performance 3-D Time-Varying Formation Control of Underactuated AUVs Under Input Saturations and Communication Delays. IEEE J. Ocean. Eng. 2023, 48, 649–662.
- 19.
Wang, W.; Wen, T.; He, X.; et al. Path Following with Prescribed Performance for Underactuated Autonomous Underwater Vehicles Subjects to Unknown Actuator Dead-Zone. IEEE Trans. Intell. Transp. Syst. 2023, 24, 6257–6267.
- 20.
Chen, G.; Dong, J. Approximate Optimal Adaptive Prescribed Performance Fault-Tolerant Control for Autonomous Underwater Vehicle Based on Self-Organizing Neural Networks. IEEE Trans. Veh. Technol. 2024, 73, 9776–9785.
- 21.
Wang, Y.; Yang, Y.; Li, Y.; et al. Fixed-Time Prescribed Performance Control for Trajectory Tracking of Underactuated AUVs Under Thrust Saturation. Ocean Eng. 2026, 344, 123455.
- 22.
Zhang, H.; Hu, Y.; Song, Z. Event-Triggered Adaptive Fault-Tolerant Control with Pre-Specified Performance for AUVs Trajectory Tracking. Ocean Eng. 2024, 313, 119372.
- 23.
Shi, Y.; Xie, W.; Zhang, G.; et al. Event-Triggered Quantitative Prescribed Performance Neural Adaptive Control for Autonomous Underwater Vehicles. IEEE Trans. Syst. Man Cybern. Syst. 2024, 54, 3381–3392.
- 24.
Liu, H.; Huang, H.; Tian, X.; et al. Distributed Optimal Formation Control for UAV-USV Multiagent Systems: A FEWNN-Based RL Approach with Self-Adjusting Prescribed Performance. Ocean Eng. 2026, 353, 124707.
- 25.
Wang, Y.; Wang, H.; Zhu, J.; et al. Flexible Prescribed Performance-Based Approaching Control for UAV Aerial Recovery Under Multiwind Disturbances. Chin. J. Aeronaut. 2025, 38, 103282.
- 26.
Guan, Y.; Xia, Y.; Geng, Z.; et al. Unified Flexible Prescribed Performance Control for Actuator-Constrained Systems Through an Event-Triggered Mechanism. Chaos Solitons Fractals 2025, 201, 117216.
- 27.
Ba, D.; Li, Y.; Tong, S. Fixed-Time Adaptive Neural Tracking Control for a Class of Uncertain Nonstrict Nonlinear Systems. Neurocomputing 2019, 363, 273–280.
- 28.
Deng, H.; Krstic, M. Stochastic Nonlinear Stabilization I: A Backstepping Design. Syst. Control Lett. 1997, 32, 143–150.
- 29.
Zuo, Z. Nonsingular Fixed-Time Consensus Tracking for Second-Order Multi-Agent Networks. Automatica 2015, 54, 305–309.
- 30.
Lei, J.; Meng, T.; Li, D.; et al. Switched Hybrid Control for Spacecraft Attitude Control with Flexible and Guaranteed Performance. IEEE Trans. Control Syst. Technol. 2025, 33, 582–596.
- 31.
Chen, C.; Zou, W.; Xiang, Z. Event-Triggered Connectivity-Preserving Formation Control of Heterogeneous Multiple USVs. IEEE Trans. Syst. Man Cybern. Syst. 2024, 54, 7746–7755.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Suite 4002 Level 4, 447 Collins Street, Melbourne, Victoria 3000, Australia
General Inquiries: info@sciltp.com