Fault Tolerant Control for Dynamic Positioning of Unmanned Marine Vehicles Based on T-S Fuzzy Model With Unknown Membership Functions

TLDR

Unmanned marine vehicles operating in complex ocean environments are modeled as Takagi‑Sugeno fuzzy systems with unknown membership functions, rendering traditional sliding‑mode control infeasible and causing conservativeness due to time‑varying delays. The study proposes a fault‑tolerant dynamic‑positioning strategy for unmanned marine vehicles that employs a quantized sliding‑mode controller with a switching mechanism to mitigate thruster faults. The method integrates a quantized sliding‑mode controller with a switching mechanism and an expanded dynamic quantization parameter adjustment that accounts for time delay and fault factors to sustain vehicle positioning. Simulation comparisons confirm the effectiveness of the proposed fault‑tolerant control approach.

Abstract

This paper proposes a novel fault tolerant control strategy for dynamic positioning of unmanned marine vehicles using the quantized feedback sliding mode control technique. Due to the complex ocean environment, the unmanned marine vehicles are modeled as the Takagi-Sugeno fuzzy system with unknown membership functions. When the membership functions are not available, traditional sliding mode control technique becomes infeasible. To tackle this difficulty, a novel quantized sliding mode control strategy based on switching mechanism is designed to compensate for thruster faults effects. In addition, the phenomenon of time-varying delay leads to conservativeness of the existing dynamic quantization parameter adjustment strategy. Then a larger quantization parameter adjustment range, by taking time delay and fault factor into account, is given. Combining the novel sliding mode controller design and the improved dynamic quantization parameter adjustment strategy, the dynamic positioning of unmanned marine vehicles with thruster faults and quantization can be maintained. Finally, the effectiveness of the proposed method is verified through the simulation comparison results.