Research On Fault Diagnosis And Fault-Tolerant Control For AUV

In the recent years, with the development of science and ocean research and exploitation and the need of national defense, higher request is put forward for the intelligent level of Autonomous Underwater Vehicle (AUV), which is an important component of ocean high-tech. As the condition which AUV works in is bad and the environment is complex and changeful, it is important to design a reliable Tolerant-control system to ensure it work safety. Fault tolerant control (FTC) schemes compensate influence of faults automatically in presence of faults such that stability can be guaranteed and dynamic performance can be recovered as possible in the post-fault systems, and the systems run stable. Hence, FTC schemes provide new ways to improve the reliability and security of complex systems.The purpose of this thesis is to realize automatic fault diagnosis and fault-tolerant of AUV control system, and to prevent control performance degraded and fault extended, and then to improve the viability and motion performance of AUV at complex sea circumstance.The main content studied in this thesis is as follow:First, the latest development and study method of fault detection and diagnosis and FTC is briefly introduced. Second, motion model of an AUV is constructed with a well-optimized Elman network, and the difference between the output of neural network and the real state value is used for fault diagnosis. Third, three types of fault of no-redundancy sensors are analyzed and the FTC strategy is considered respectively. Finally, a strategy of thruster reconstruction is developed for FTC system. All the approaches discussed in this thesis are demonstrated through corresponding simulations.