Signal processing method for autonomous underwater robot based on particle swarm optimization monostable adaptive stochastic resonance

Abstract

The invention provides an autonomous underwater robot signal processing method based on particle swarm optimization monostable adaptive stochastic resonance. The structure parameters of a monostable stochastic resonance system are optimized through a particle swarm optimization algorithm so as to realize the adaptive stochastic resonance of AUV (Autonomous Underwater Vehicle) control signals and status signals and improve the stochastic resonance effect of the AUV control signals and status signals, and finally the purposes of inhibiting external stochastic disturbance contained in the AUV control signals and status signals and enhancing the characteristics of fault signals are achieved through the phenomenon of stochastic resonance. The method solves the problems that the selection of the structure parameters lacks reasonable theoretical foundation and an optimal stochastic resonance effect is difficult to realize caused by the fact that a traditional single-parameter fixed-step adaptive stochastic resonance method ignores the interaction effect among the parameters, the external disturbance is inhibited and the characteristics of the fault signals are enhanced through the AUV control signals and status signals processed by an adaptive stochastic resonance system, and the method can be used in the fields such as fault diagnosis and fault-tolerant control of AUV thrusters.

Description

technical field [0001] The invention relates to an autonomous underwater robot propeller fault diagnosis and fault-tolerant control method. Background technique [0002] With the dwindling land resources, the pace of human development of the ocean is getting faster and faster. Autonomous underwater vehicle (AUV: Autonomous Underwater Vehicle) is currently the only carrier that can detect and develop in the deep sea without human beings, and has been highly valued by researchers at home and abroad. The propeller is the most important executive part of AUV and has the heaviest load. Once it fails, it will directly affect the safety of AUV. Fault diagnosis of AUV thruster status is an important technical means to improve the safety of AUV. [0003] Due to the influence of external interference, the direct use of AUV control signals and status signals collected by the sensor for fault diagnosis is not effective, and there are problems of easy false detection and missed detecti...

AI Technical Summary

Problems solved by technology

However, in the process of studying the stochastic resonance of AUV signals, it is found that the coupling of external interference and real fault signals in AUV signals is difficult to separate, and the method of adding noise is difficult to achieve its stochastic resonance; the adjustment strategy of fixing one parameter and adjusting another parameter can realize AUV Signal stochastic resonance, but because only a single parameter is adaptively adjusted, and the interaction between parameters is ignored, there is a problem that the selection of stochastic resonance system parameters lacks a reasonable theoretical basis and it is difficult to achieve the optimal stochastic resonance effect

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