Immune memory learning control based wet coagulation bath temperature control process for carbon fiber precursor

Abstract

The invention provides an immune memory learning control based wet coagulation bath temperature control process for a carbon fiber precursor. The process route is as follows: polyacrylonitrile original liquid is extruded into a coagulation bath tank through a spinneret plate, the temperature of coagulating liquid in the coagulation bath tank is subjected to real-time detection by a temperature detecting element and is fed back to a controller, the controller carries out current control quantity calculation according to the current and historical data of set value input, control quantity and feedback output and outputs a current control quantity to a controlled object, a coagulation bath is heated, and finally, the actual temperature of the coagulation bath reaches a set temperature. The controller is an intelligent temperature controller based on immune memory learning and is used for simulating an immune recognition, response and memory mechanism of a human body immune system, the traditional iterative learning control algorithms are improved, interference is taken as an antigen and is subjected to recognition, elimination and feature memory, and a control system can quickly respond and accurately control interference when the same interference occurs again, so that the stability and interference immunity of the control system are further improved.

Description

technical field [0001] The invention belongs to the technical field of automatic control, in particular to a carbon fiber precursor wet coagulation bath temperature control process based on immune memory learning control. Background technique [0002] Carbon fiber is a high-temperature-resistant fiber with high strength and modulus, and it is a high-end variety of chemical fibers. The biggest feature of carbon fiber is that it is light and hard, so it has a wide range of uses. In the production process of carbon fiber, experts at home and abroad agree that the quality of polyacrylonitrile fiber as carbon fiber precursor is an important factor restricting the performance of carbon fiber. Therefore, how to further improve the quality of polyacrylonitrile precursor has been widely concerned by scholars at home and abroad. [0003] The production process of polyacrylonitrile precursors has very high requirements on the control accuracy of the environment and equipment. A sligh...

AI Technical Summary

Problems solved by technology

[0003] The production process of polyacrylonitrile precursors has very high requirements on the control accuracy of the environment and equipment. A small disturbance will cause the quality of the precursor fibers to be uneven, thereby affecting the quality of carbon fiber multifilaments

However, in complex industrial production processes such as the production of carbon fiber precursors, there are often many physical and chemical process mechanisms that cannot be expressed by accurate mathematical models, such as diffusion, coagulation and deformation during the solidification of viscoelastic fluids.

These processes interact and restrict each other, and it is impossible to establish an accurate mathematical model. Often, the control system can only be designed by establishing an approximate model or using a fitting model such as an empirical formula.

This will introduce large errors to the traditional model-based control system, resulting in the inability to achieve high-precision control in these complex chemical processes

Images