Composite anti-interference trajectory tracking control algorithm for backward process of unmanned rolling machine

A trajectory tracking and unmanned driving technology, which is applied to controllers with specific characteristics, electric controllers, etc. to improve accuracy, enhance anti-interference ability, and improve robustness.

Active Publication Date: 2021-06-18
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problem that the control method of the unmanned rolling machine in the prior art cannot include fast small-scale interference and slow large-scale interference, and to provide a layering of the unmanned rolling machine back process Hierarchical self-learning composite anti-disturbance trajectory tracking control algorithm

Method used

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  • Composite anti-interference trajectory tracking control algorithm for backward process of unmanned rolling machine
  • Composite anti-interference trajectory tracking control algorithm for backward process of unmanned rolling machine
  • Composite anti-interference trajectory tracking control algorithm for backward process of unmanned rolling machine

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Embodiment 1

[0046] A layered hierarchical self-learning compound anti-disturbance trajectory tracking control algorithm for the backward process of an unmanned rolling machine, comprising the following steps:

[0047] Step 1, the reconstructor for the position and heading of the rear body, calculates the measured value of the heading angle of the rear body of the vehicle and the position of the rear body, obtains the heading and position of the reconstructed rear body, and then calculates the rolling machine according to the target trajectory of the rolling machine. The actual distance error in the trajectory tracking of the press;

[0048] Step 2, the anti-disturbance controller of the distance error calculates the target heading angle of the rolling machine through the total disturbance of the actual distance error obtained in step 1 and the distance error obtained by the instant disturbance observer, so that the trajectory tracking distance of the rolling machine is error tends to zero...

Embodiment 2

[0052] As a preferred solution, the anti-disturbance controller of the distance error in the step 2 will use the ideal heading angle (θ 2 ) and the actual distance error (e d ) is simplified as a range error dynamic system model, and the deviation between the range error dynamic system model and the actual process is unified as the total disturbance of the range error (f outlp ), put f outlp It is regarded as an extended state in the distance error dynamic system model, that is, the dynamic system model is extended to a dynamic system with a higher order than the original dynamic system model. Using the real-time disturbance observer, using the actual heading angle and actual distance error information, the total disturbance to the distance error (f outlp ) for real-time estimation and real-time compensation in the range error perturbation suppressor. For the system processed by the range error disturbance suppressor, the range error feedback controller is designed, and by ...

Embodiment 3

[0056] As the basis for the development of the control algorithm, the prediction model of the front and rear body angle, heading angle and position of the roller compactor is established first. Although this part of the content is not the content of the present invention, it is still written here for the sake of completeness. In this embodiment, the following simplified heading angle dynamic system model is adopted, but it is not limited to this model. The prediction model of the influence of the steering wheel of the roller compactor on the articulation angle of the front and rear body can be expressed by (1).

[0057]

[0058] Among them, γ is the articulation angle of the front and rear body (unit: radian), is the derivative of the articulation angle of the front and rear body with respect to time, is the target rotation angle of the steering wheel (unit: radian), τ steer is the time constant of the dynamic process of the steering system (unit: second), a is the stati...

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Abstract

The invention discloses a composite anti-interference trajectory tracking control algorithm for a backward process of an unmanned rolling machine. The algorithm comprises the following steps that: the course and position of a rear vehicle body are reconstructed, and an actual distance error in trajectory tracking of a rolling machine is calculated; an anti-interference controller of the distance error is combined with the total disturbance of the distance error obtained by an instant disturbance observer to calculate the target course angle of the rolling machine, so that the trajectory tracking distance error of the rolling machine tends to zero; a course angle anti-interference controller calculates a target steering wheel turning angle of the rolling machine through the target course angle obtained in the step 2, course total disturbance obtained by the instant disturbance observer and course angle disturbance obtained based on a model parameter learning device, so that the actual course angle of the rolling machine approaches the target course angle obtained in the step 2; and the target steering wheel angle obtained in the step 3 is sent to a steering wheel angle controller. The control algorithm can solve the problems of rapid small-range interference and slow large-range interference.

Description

technical field [0001] The invention relates to the technical field of unmanned rolling machine control, in particular to a layered and hierarchical self-learning composite anti-disturbance trajectory tracking control algorithm for the unmanned rolling machine backing process. Background technique [0002] The accurate tracking of the target driving trajectory by the unmanned rolling machine is the key to ensuring the quality, efficiency and safety of the rolling operation. Traditional PID (feedback-integral-derivative) control is one of the most widely used control algorithms. For example, Zhang et al. from Tsinghua University and Bian Yongming from Tongji University have used PID feedback control for the track tracking control of rolling machines. However, PID feedback control will take control action only after a significant trajectory tracking error is produced. This passive control method of "after-event adjustment" can easily cause the phenomenon of "drawing dragons"...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B11/42
CPCG05B11/42
Inventor 宋康谢辉
Owner TIANJIN UNIV
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