Unmanned ship course active-disturbance-rejection control system and control method thereof

Abstract

The invention relates to an unmanned ship course active-disturbance-rejection control system based on a fuzzy neural network and a control method thereof, and the system comprises a linear active-disturbance-rejection control module and a fuzzy neural network module.The self-learning function of the fuzzy neural network is utilized to solve the problem that parameters need to be debugged through certain groping experience in fuzzy control, meanwhile, control parameters of the active disturbance rejection controller can be adjusted in a self-adaptive mode, and external disturbance of the unmanned ship and compensation of internal disturbance of the system at the control quantity can be well estimated through a linear expansion state observer; and the observer bandwidth is used as a unique parameter, so that the parameter setting difficulty is reduced.

Description

technical field [0001] The invention relates to a fuzzy neural network-based automatic disturbance rejection control method for an unmanned boat heading, and belongs to the technical field of unmanned boat heading control. Background technique [0002] In recent years, with the exploration and development of marine resources, marine security has been paid more and more attention by people. Unmanned surface vehicle, referred to as unmanned vehicle, is a surface robot that can monitor the marine environment, maintain marine rights and interests, and be used in modern military operations. With the advancement of technology, its application range is expanding day by day. It has also gradually increased, especially in some scenarios that are not suitable for human operations, such as detecting important hydrological data in waters with nuclear and chemical pollution. Therefore, it has broad application prospects and has become a research hotspot for intelligent marine equipment a...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the problems of weak anti-jamming ability and low control precision in the course control of unmanned boats by traditional control methods, and combine the advantages and disadvantages of active disturbance rejection control to propose an unmanned boat based on fuzzy neural network. The course control method ensures that the unmanned vehicle can track the desired course well under the conditions of external environmental disturbance and system internal disturbance, and relies on the fuzzy neural network to optimize the parameters in the ADRC unit to improve the performance of the ADRC controller. Self-adaptive ability, reducing the difficulty of parameter setting

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