Visual servo control method and system using grey prediction model

A gray prediction model and visual servo technology, applied in the field of communication, can solve the problem of untimely control and achieve the effect of precise flight control

Active Publication Date: 2021-03-09
SHENZHEN TECH UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] The technical problem to be solved by the present invention is to provide a visual servo control method and system using a gray prediction model to solve the existing control method of flying robots, through Judging whether the system behavior meets the predetermined requirements and then controlling it, there is a problem of untimely control

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  • Visual servo control method and system using grey prediction model
  • Visual servo control method and system using grey prediction model

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Embodiment 1

[0053] see figure 1 , figure 1 It is a schematic flowchart of a visual servoing control method using a gray prediction model provided by an embodiment of the present invention.

[0054] Such as figure 1 As shown, the first embodiment of the present invention provides a visual servoing control method using a gray prediction model, including the following steps S1 to S4.

[0055] S1. Obtain the actual position of the target collected by the airborne image acquisition device of the drone and the expected position corresponding to the actual position of the target;

[0056] S2. Calculate an output deviation value according to the target actual position and the expected position;

[0057] S3. Obtain the predicted value of the next state of the drone through the gray prediction module;

[0058] S4. Comparing the output deviation value with the prediction value to obtain a prediction error, and controlling the UAV according to the prediction error.

[0059] Here, the onboard ima...

Embodiment 2

[0061] It also includes control parameters to control the attitude, angle and speed of the UAV flight. After calculating the output deviation value according to the actual position of the target and the expected position, visual servo control is also included, and the visual servo control includes:

[0062] Obtaining the image feature error between the actual position of the target and the expected position of the drone flying, and establishing a servo relationship between the image feature error and the speed;

[0063] The position controller is used to calculate the speed control law according to the servo relationship, and the desired attitude is obtained through the speed control law;

[0064] The attitude tracking control of UAV is carried out by sliding mode control.

[0065] Specifically, see figure 2 and image 3 , figure 2 It is a flow chart of image-based visual servoing control according to the second embodiment of the present invention. image 3 It is a visu...

Embodiment 3

[0067] The gray prediction module includes a GM(1,1) model, and the GM(1,1) model performs position accuracy prediction through an adjustment factor.

[0068] Specifically, see Figure 4 , Figure 4 It is the basic frame diagram of the gray prediction module of the third embodiment of the present invention. Propose an improved gray prediction model based on the background value of the adjustment factor. The traditional GM (1,1) model is more widely used in the gray prediction theory. The present invention proposes a new background value with an adjustment factor and changes the initial condition. Combined with the new GM(1,1) model, the optimization method of the adjustment factor is proposed, and it is applied to the modeling of the visual servo control system of the flying robot. The new model has passed the simulation and prediction comparison of the pure exponential sequence. It can be seen that the new model of GM(1,1) optimized by the adjustment factor has higher accur...

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Abstract

The invention provides a visual servo control method, system and device utilizing a gray prediction model and a storage medium. The method comprises the steps of acquiring a target position collectedby an airborne image collection device of an unmanned aerial vehicle and an expected position corresponding to the target position; performing visual servo control according to the output values of the target position and the expected position; obtaining a predicted value of the next state of the unmanned aerial vehicle through a gray prediction module; and comparing the output value with the prediction value to obtain a prediction error, and continuously adjusting the operation of the unmanned aerial vehicle to enable the unmanned aerial vehicle to achieve advanced flight control. The operation control error of the next state of the flying robot is predicted through the gray prediction model and compared with a given error, switching of different PID control parameters is completed, and therefore the moving process of the flying robot is controlled in advance, position and attitude information is continuously corrected in the flying process, and more accurate flying control is achieved.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a visual servo control method and system using a gray prediction model. Background technique [0002] In actual industrial control, with the continuous development of industrial technology, as well as the complexity, time-varying and uncertainties of industrial processes, traditional industrial control methods are difficult to meet the requirements of modern industry, so people gradually study intelligent control theory . Fuzzy control, predictive control, and probability statistics are common control methods for uncertain systems. However, due to the complexity and time-varying nature of the system, it is difficult to establish an effective mathematical model, so the predictive control based on the precise model of the system cannot meet the requirements of control. For some new systems or complex systems, there is not much experience and a large amount of histo...

Claims

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Application Information

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IPC IPC(8): G05D1/08G05D1/10
CPCG05D1/0808G05D1/101Y02T10/40
Inventor 程涛邓启超
Owner SHENZHEN TECH UNIV
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