Pneumatic servo system self-adaptive neural network control method considering state limitation

A neural network control and servo system technology, which is applied in the field of high-precision position tracking control of pneumatic position servo systems, can solve the problems of inaccurate model zero point and limited state, and achieve the effect of effective control, high tracking accuracy, and reduction of unknown disturbances.

Active Publication Date: 2021-06-15
XIAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide an adaptive neural network control method for a pneumatic servo system considering the state limitation, focusing on the problem of the state limitation of the pneumatic position servo system, and comprehensively considering the unknown model of the pneumatic system, the unknown control gain and the unknown disturbance and the inaccurate zero point of the valve and other influencing factors, because more practical constraints are considered, better control accuracy is obtained

Method used

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  • Pneumatic servo system self-adaptive neural network control method considering state limitation
  • Pneumatic servo system self-adaptive neural network control method considering state limitation
  • Pneumatic servo system self-adaptive neural network control method considering state limitation

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Embodiment

[0123] In this embodiment, the product models selected by the main components in the pneumatic system are:

[0124] Cylinder 3 adopts the model DGPL-25-450-PPV of FESTO Company;

[0125] The model used by the proportional valve 7 is MPYE-5-1 / 8-HF-010-B;

[0126] The model used by the position detection element 1 is MLO-POT-450-5TLF;

[0127] The model used by the data acquisition card is PCI2306;

[0128] The model that computer 13 adopts is that CPU is P21.2GHz, and the control software built-in in computer adopts VB to compile, shows the change curve of relevant variable in the control process through the screen.

[0129] The control objectives of this embodiment are respectively set as

[0130] Reference signal 1: The sinusoidal signal is:

[0131] the y d =A 1 sin ω 1 t (24)

[0132] Among them, A 1 = 111.65, ω 1 =0.5π.

[0133] The expression of the S-curve signal is:

[0134] the y d =-(A 2 / ω 2 )sin(ω 2 t)+(A 2 / ω 2 )t (25)

[0135] Among them, A 2 ...

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Abstract

The invention discloses a pneumatic servo system self-adaptive neural network control method considering state limitation. The method is specifically implemented according to the following steps: step 1, modeling a pneumatic position servo system; and step 2, setting a self-adaptive neural network controller of the pneumatic system, defining a Nussbaum function for solving the problem that the control direction of the system is unknown, outputting a signal u of the controller through a D / A converter, and adjusting the displacement of a piston of the pneumatic system in real time. According to the method, the self-adaptive neural network controller of the pneumatic position servo system considering the state limitation is designed, the obstacle Lyapunov function is introduced to prove the stability of the state limitation system, and unknown object model, unknown control direction, uncertain proportional valve zero point and other internal and external disturbances are comprehensively considered; and finally a controller and a parameter self-adaptive law for ensuring the stability of the system are obtained.

Description

technical field [0001] The invention belongs to the technical field of high-precision position tracking control of a pneumatic position servo system, and relates to an adaptive neural network control method of a pneumatic servo system considering state limitation. Background technique [0002] The pneumatic servo system (that is, the pneumatic position servo system, hereinafter referred to as the pneumatic 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, and is the most automated and mechanized production process. One of the effective means, pneumatic technology has become an indispensable basic part in many fields. [0003] Pneumatic devices on industrial production lines are usually required to be able to achieve high-precision position tracking control. The system is essentially a nonlinear system. If the state limit is not considered, the contro...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 任海鹏焦姗姗李洁邓毅
Owner XIAN UNIV OF TECH
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