A neural network-based deep-water crane uncertainty control method and system

Abstract

The application provides a kind of deepwater crane uncertainty control method and system based on neural network, it is related to vibration control technical field, method includes: obtaining the dynamic characteristics of deepwater crane;Deepwater crane dynamics model is constructed;Based on the dynamics model, construct the controller based on adaptive neural network;According to the controller based on adaptive neural network, construct the Lyapunov function of deepwater crane system;According to Lyapunov function, verify the stability of deepwater crane system;Determine whether the verification result meets the preset stability requirement;If yes, digital simulation is carried out on deepwater crane system;Otherwise, the gain parameter of the controller is corrected;Through simulation software, digital simulation is carried out on deepwater crane system, and simulation result is obtained;Determine whether the control effect of simulation result meets the expectation;If yes, keep gain parameter;Otherwise, the gain parameter of the controller based on adaptive neural network is optimized.

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