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.

中文翻译：

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基于隶属函数未知的TS模糊模型的无人机动态定位容错控制

提出了一种基于量化反馈滑模控制技术的无人机动态定位容错控制策略。由于复杂的海洋环境，无人驾驶飞行器被建模为具有未知隶属函数的Takagi-Sugeno模糊系统。当隶属函数不可用时，传统的滑模控制技术变得不可行。为了解决这一难题，设计了一种基于切换机制的新型量化滑模控制策略来补偿推进器故障影响。另外，时变时滞现象导致了现有动态量化参数调整策略的保守性。然后，通过考虑时间延迟和故障因素，给出了较大的量化参数调整范围。结合新颖的滑模控制器设计和改进的动态量化参数调整策略，可以保持带有推进器故障的无人驾驶船舶的动态定位和量化。最后，通过仿真比较结果验证了该方法的有效性。