Device for self-correcting control for multi-model RBF neural network of deep submersible rescue vehicle and method thereof

Abstract

The invention provides a device for self-correcting control for a multi-model RBF neural network of a deep submersible rescue vehicle and a method thereof. The device comprises an electric compass, three high-frequency short baseline sonars, a DSP data processing system, a control computer, two vertical channel propellers, two horizontal channel propellers and two main propellers, wherein the three high-frequency short baseline sonars are connected with the DSP data processing system; the controlling computer is embedded with a thrust allocation logic, a filter and an algorithm for the self-correcting control for the multi-model RBF neural network; the electric compass is connected with the control computer by a serial port; the control computer is connected with the two vertical channel propellers, the two horizontal channel propellers and the two main propellers by a digital-analog conversion card of the control computer; and the DSP data processing system is connected with the control computer by a serial port. The invention has high control precision and can successfully complete the butt joint of the deep submersible rescue vehicle and a disabled submarine.

Description

technical field [0001] The invention relates to a deep submersible lifeboat control device. In particular, a multi-mode RBF neural network self-correction control device. The invention also relates to a control method for a deep submersible lifeboat. Background technique [0002] At present, the dynamic positioning system of the ship mostly adopts the PID control algorithm, so that the ship or the deep submersible lifeboat can be dynamically maintained at a certain desired position. Although the PID controller is simple in design and has good control performance in the design working conditions, PID control has many limitations, mainly reflected in the fact that the control effect will become poor or even unstable when the environment changes and deviates from the design working conditions. However, in the docking process of the deep submersible lifeboat and the wrecked submarine, the marine environment is relatively complicated, and there are often many interference facto...

AI Technical Summary

Problems solved by technology

This method describes a ship dynamic positioning control method based on fuzzy adaptive algorithm. The system adjusts the fuzzy control rules to achieve the best through the information in the control process, so as to achieve the purpose of self-adaptation. This method exists in the control System static difference

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