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Network control system time delay compensation method based on predictive control

A technology of network control system and time delay compensation, applied in general control system, control/regulation system, program control, etc., can solve the problems of complex analysis of network control system, etc.

Pending Publication Date: 2019-06-04
QINGDAO TECHNOLOGICAL UNIVERSITY
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The introduction of the network in the control loop makes the analysis of the network control system more complicated, especially the induced delay in the network has an important impact on the performance of the system
At present, there is no method to accurately predict and effectively compensate the time delay of networked control systems

Method used

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  • Network control system time delay compensation method based on predictive control
  • Network control system time delay compensation method based on predictive control
  • Network control system time delay compensation method based on predictive control

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Embodiment Construction

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0035] The invention provides a network control system time delay compensation method based on predictive control, which can realize accurate prediction and effective compensation of network control system time delay, and has good development prospects.

[0036] 1 Fuzzy neural network optimized based on particle swarm optimization

[0037] 1.1 Fuzzy neural network model

[0038] Fuzzy neural network is the product of the combination of fuzzy set theory and neural network. It not only has the large-scale parallel processing ability, self-learning ability and self-adaptive ability of neural network, but also can process fuzzy information and complete fuzzy reasoning function, with superior performance.

[0039] The prediction model is a 4-layer network model with multiple input...

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Abstract

The invention discloses a network control system delay compensation method based on predictive control. The method comprises the steps that (1) random delay data in a network control system are acquired and preprocessed; (2) a fuzzy neural network optimized by a particle swarm algorithm is used to predict the current delay; (3) the predicted delay is compensated by an implicit PIGPC algorithm; and(4) a clock in the network control system determines whether specified work end time is reached, and if so, the method ends, and otherwise returning to step (2) is carried out. The method disclosed by the invention can realize accurate prediction and effective compensation for the delay of the network control system, and has a good development prospect.

Description

technical field [0001] The invention relates to the field of network control systems, in particular to a predictive control-based network control system delay compensation method. Background technique [0002] The network control system refers to the closed-loop feedback control system formed by the actuators, sensors and controllers in the control system exchanging information through the network. The introduction of the network in the control loop makes the analysis of networked control systems more complicated, especially the induced delay in the network has an important impact on the performance of the system. At present, there is no method that can accurately predict and effectively compensate the time delay of networked control systems. Contents of the invention [0003] In order to solve the above technical problems, the present invention provides a network control system time delay compensation method based on predictive control, so as to achieve accurate predicti...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/0285G06N3/086G06N3/088G06N3/006G05B19/4185G05B2219/37512Y02P90/02G06N3/043G06F17/11G05B13/048
Inventor 赵景波薛秉鑫王众朱敬旭辉邱腾飞刘信潮
Owner QINGDAO TECHNOLOGICAL UNIVERSITY
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