Improved Long Short-Term Memory-Based Fixed-Time Fault-Tolerant Control for Unmanned Marine Vehicles with Signal Quantization

• Published in: Journal of marine science and engineering Vol. 13; no. 10; p. 2012
• Main Authors: Yang, Xin, Hao, Li-Ying, Wang, Jia-Bin, Dong, Gege, Li, Tieshan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 20.10.2025
• Subjects: Adaptive algorithms; Controllers; Disturbances; Dynamic positioning; Fault tolerance; Long short-term memory; Neural networks; Optimization algorithms; Performance degradation; Sliding mode control; State observers; Thrusters; Unmanned vehicles; Vehicles
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse13102012

This paper presents a fixed-time fault-tolerant control strategy based on an improved long short-term memory network for dynamic positioning of unmanned marine vehicles subject to signal quantization, disturbances, and input saturation. Firstly, an improved long short-term memory network optimized by an adaptive mixed-gradient algorithm is developed to accurately estimate external disturbances. Secondly, a fixed-time extended state observer is designed to rapidly predict thruster faults. Subsequently, within a fixed-time control framework, a novel terminal sliding-mode surface incorporating signal quantization parameters is constructed. In addition, a dynamic uniform quantization strategy with tunable sensitivity is introduced to effectively alleviate the performance degradation induced by quantization errors. Based on this, a fixed-time fault-tolerant controller is constructed. Finally, simulation results and comparative experiments are provided to demonstrate the effectiveness of the proposed control scheme.