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Full-hovering hovercraft course control method based on grey prediction hybrid genetic algorithm-PID

A hybrid genetic algorithm and gray prediction technology, applied in two-dimensional position/channel control, adaptive control, general control system, etc., can solve problems such as difficult to obtain maneuverability, achieve good dynamic adjustment quality, meet accuracy, The effect of improving adaptive ability

Inactive Publication Date: 2017-05-24
HARBIN ENG UNIV
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Problems solved by technology

However, due to the nonlinear characteristics of the system itself, it is difficult to obtain good maneuverability

Method used

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  • Full-hovering hovercraft course control method based on grey prediction hybrid genetic algorithm-PID
  • Full-hovering hovercraft course control method based on grey prediction hybrid genetic algorithm-PID
  • Full-hovering hovercraft course control method based on grey prediction hybrid genetic algorithm-PID

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Embodiment Construction

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] The purpose of the present invention is achieved by the following steps:

[0045] 1. Obtain the position and attitude parameters of the hovercraft:

[0046] The position information of the full-lift hovercraft is measured by the position reference system, and the heading attitude data information of the full-lift hovercraft is measured by the attitude reference system; the acquired attitude and position signals of the full-lift hovercraft are filtered and fused to obtain the full The precise position and attitude of the pad-lifted hovercraft.

[0047] 2. Heading control of hybrid genetic algorithm-PID heading controller

[0048] in the attached figure 2 Among them, r is the given course, e is the error, u is the output of the PID controller, y is the actual course of the hovercraft, and the function of the genetic algorithm module is to adjust the PID parame...

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Abstract

The invention provides a full-hovering hovercraft course control method based on a grey prediction hybrid genetic algorithm-PID. The method comprises the following steps: the actual position of a full-hovering hovercraft is measured through a position reference system, and the actual heading attitude of the full-hovering hovercraft is measured through an attitude reference system; grey error prediction is carried out, namely, a metabolic model is built, and future behavior data is predicted according to the actual position and the actual heading attitude to get advanced control values; a PID controller compares input expected position and heading attitude with the advanced control values obtained by grey error prediction, and calculates out an error signal for control of a full-hovering hovercraft course control system; and the PID controller is set online by use of a hybrid genetic algorithm. The method is of strong adaptability to hovercraft course control, and can achieve a good effect in all kinds of environments. The driver's manipulation burden can be reduced, and the control quality can be improved.

Description

technical field [0001] The invention relates to a method for controlling the heading of a full-cushion lift hovercraft. Background technique [0002] The full lift hovercraft is a high-performance ship with good speed and amphibiousness, and has a wide range of applications. However, due to the nonlinear characteristics of the system itself, it is difficult to obtain good maneuverability. In order to control and improve the dynamic characteristics and obtain precise control laws, a hybrid genetic algorithm-PID method using gray prediction is proposed, and the genetic algorithm is used to optimize and adjust the PID parameters online at each sampling time. At the same time, the gray error prediction can accurately predict the real-time error The change trend, PID control with the error prediction value can play a role of advanced control to improve the maneuverability of the hovercraft, reduce the driver's manipulation burden, and improve the control quality at the same time...

Claims

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Application Information

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IPC IPC(8): G05D1/02G05B13/04
CPCG05D1/0206G05B13/042
Inventor 王元慧蒋希赟付明玉王成龙张放赵亮博
Owner HARBIN ENG UNIV
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