Research On Motion Control And Fault Diagnosis Of Underwater Vehicle

21 century is the century which human develop and utilize ocean. Ocean is the seedbed and resource treasury of human being and it will play great roll in the development of economics and society. "The people who control ocean and master the development technology of ocean resource will control the future resource treasury", these words show the important value of ocean. As the important instrument of knowing and utilizing the ocean resource, underwater vehicle will display its potential usage in ocean development and maritime application. Motion control and fault detection and diagnosis (FDD) are the core technologies of underwater vehicle, and it has crucial theory and practical engineering worth. The main purpose of this dissertation is to propose better motion control algorithms and realize the FDD of control system so as to enhance the motion control performance and life-force of underwater vehicle.The author undertakes the dissertation research with the title of "Research on Motion Control and Fault Diagnosis of Underwater Vehicle". We introduced the basic configuration of the research plant and hardware and software architectures, and the motion model in six-degree freedom was built up. All those will establish the theory foundation for the following passages. The federated kalman filtering technology was studied in order to improve the precision and reliability of combined navigation of underwater vehicle. Based on the information conservation principle, the federated kalman filtering algorithm was deduced and its optimization was demonstrated. The federated kalman filter was adapted for the combined navigation of underwater vehicle, and the feasibility of the federated kalman filter was verified by the experiment results. The typical S-plane controller has certain steady state error when the system is stable; therefore, the intelligent integral was brought in to decrease the steady state error. The expert system was brought in S-plane controller to construct the expert S-plane controller. We use the expert experience for reference, and the control effect was improved. Comparing between the typical S-plane controller and the capacitor-plate model controller, the generalized S-plane controller was presented. Different S-plane controller can be obtained by substitute different S type nonlinear function for Sigmoid function in typical S-plane controller. The analyzing conclusion can direct controller designing. Aiming at the bad robustness of fault detection and diagnosis (FDD) based on analytic model; the sliding mode idea was introduced to enhance the robustness of FDD. The threshold method can cause erroneous judgement because of its own defects; therefore, here we use fuzzy reasoning method to analyze the residual data so as to overcome the shortcoming of the threshold method. Plenty of simulation results told us that the residual analyzing method based on fuzzy reasoning can distinguish between the state adjustment and the state abnormity of underwater vehicle; accordingly, the precision and robustness of FDD were increased. Aiming at the disadvantage of neural network, we combined the fuzzy logic and neural network. A fuzzy neural network structure was introduced, and the neural network dynamic learning rate based on minimum adjustment was deduced to make sure the present sample will has small impact to the history data. The wavelet transform is undertaken for the sensor information of the underwater vehicle, and the extreme points of the wavelet transform are used to detect the jumping faults of the signal. In order to decrease the noise's influence, the threshold method is brought in. The disturbance of the noise can be bucked by setting the threshold for the high frequency parameters of the wavelet transform. As to the oscillation of the outputs of the positioning sonar, the linear smoothing method is adopted. The cubical curve fitting and kalman filter are designed and comparison experiments are conducted among them, and the experiment results say:underwater vehicle as the specific research plant, linear smoothing method is not only very simple but also direct and effective.This dissertation undertakes plenty of simulation experiments and practical trials, and the experiment results verify the feasibility and validity of the proposed methods. The motion control algorithms can improve the control performance, and the fault detection and diagnosis algorithms can enhance the precision and robustness of FDD.