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Conventional grey GM(1,1) method might generate much large prediction errors when predicting the trend of weak thruster fault. To solve this problem, a prediction method based on improved grey prediction model is proposed. The proposed method selects the known sequence point with the minimum prediction error as the initial condition of grey derivative model, rather than first element of the known...
As the impact of underwater vehicle dynamics modeling error on fault diagnosis system, a method using improved Elman neural network to modify underwater vehicle dynamics model in the current is proposed. The neural network parameter adjustment law under the Lyapunov stability is given. Sliding mode observer is constructed for state estimation based on the modified dynamics model. The change of state...
Operating in complex ocean environment, the condition monitoring and fault diagnosis of sensors have great impact on the safety of autonomous underwater vehicle (AUV). When the sensor soft fault of AUV is detected by the traditional method of observer based on the means of close-loop control and close-loop detection, the sensor measured value with fault information is fed into the input of observer,...
To improve the reliability and intelligence of autonomous underwater vehicle, an AUV test-platform named "Beaver" is developed. The hardware and software system structure are introduced in detail. By analyzing the performance and the fault mechanism of thruster, it establishes the condition monitoring system for thrusters and sensors based on the double closed-loop PID controller, which...
This paper introduces a novel fault diagnosis system of thruster for open-frame underwater vehicles (UV). Basically, the fault diagnosis system is a control allocator, but this primary function is enhanced with the ability of automatic thruster fault detection and diagnosis. The proposed fault diagnosis system consists of two subsystems: a underwater vehicle motion condition monitoring subsystem and...
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