An Adaptive Fuzzy Neural Network Control Method for Pneumatic Position Servo System

A neural network control and fuzzy neural network technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem that the tracking control accuracy of the pneumatic position servo system is difficult to meet the requirements, so as to reduce the impact of system performance , the effect of high tracking accuracy

Active Publication Date: 2022-03-29
XIAN UNIV OF TECH
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an adaptive fuzzy neural network control method for a pneumatic position servo system, which solves the problem that the tracking control accuracy of the pneumatic position servo system is difficult to meet the requirements of the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • An Adaptive Fuzzy Neural Network Control Method for Pneumatic Position Servo System
  • An Adaptive Fuzzy Neural Network Control Method for Pneumatic Position Servo System
  • An Adaptive Fuzzy Neural Network Control Method for Pneumatic Position Servo System

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0092] In this embodiment, the product models selected for the main components in the pneumatic position servo system are:

[0093] Cylinder 3 adopts the model DGPL-25-450-PPV of FESTO Company;

[0094] The model used by the proportional valve 7 is MPYE-5-1 / 8-HF-010-B;

[0095] The model adopted by position detection element 1 is MLO-POT-450-5TLF displacement detector;

[0096] The model used by the universal data acquisition card is PCI2306, which contains figure 1 Middle A / D conversion module 12 and D / A conversion module 11;

[0097] The model that computer 13 adopts is that CPU is P2 1.2GHz, and the control software built-in in computer adopts VB to compile, shows the variation curve of relevant variable in the control process by screen display.

[0098] The control objectives of this embodiment are respectively set as

[0099] Reference signal 1: The sinusoidal signal is

[0100] the y m =A 1 sin ω 1 t (19)

[0101] Among them, A 1 = 111.65, ω 1 =0.5π.

[0102]...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an adaptive fuzzy neural network control method for a pneumatic position servo system. The steps include: step 1, establishing a model of the pneumatic position servo system, and performing linearization; step 2, setting an adaptive controller of the pneumatic position servo system ; Step 3, using the fuzzy neural network to estimate the uncertain function in the model, the fuzzy neural network is composed of two parts: an antecedent network and a posterior network. After generating the fuzzy rules, the control quantity u is obtained by combining the neural network design controller, outputting u to the proportional valve through the D / A conversion module, and adjusting the displacement of the piston of the pneumatic position servo system in real time. In the method of the invention, the uncertain zero point of the proportional valve is also processed through the adaptive law, and compared with the existing controller, the tracking accuracy of the method of the invention is higher.

Description

technical field [0001] The invention belongs to the technical field of position tracking control of a pneumatic position servo system, and in particular relates to an adaptive fuzzy neural network control method of a pneumatic position servo system. Background technique [0002] The pneumatic position servo system uses compressed gas as the working medium, and has the characteristics of no pollution, high power-to-volume ratio, simple structure, low cost, safety and reliability, etc. It is one of the most effective means of automation and mechanization of the production process. Indispensable basic part of the field. [0003] Pneumatic devices on industrial production lines are usually required to be able to achieve high-precision position tracking control. Due to the influence of factors such as the compressibility of gas, the nonlinearity of flow at the valve port, the friction of the cylinder, and the low damping characteristics of the pneumatic position servo system, Pn...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 任海鹏焦珊珊李洁
Owner XIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap