A software-defined industrial intelligent control system

Abstract

The software-defined industrial intelligent control system provided by this application can realize computing power optimization scheduling and dynamic reconstruction in a software-defined manner, allocate resources for different industrial control tasks and edge computing tasks on demand, and build a differentiated An edge intelligent controller with control and computing capabilities supports both real-time industrial control tasks and non-real-time edge intelligent computing tasks, and is of great significance for improving the utilization of industrial edge device resources, improving the overall service capability of the edge, and reducing energy consumption and actual value. In addition, it can also realize real-time control and non-real-time computing task requirements such as industrial intelligent control, edge computing, and industrial AI, and has opened up the platform capabilities of the edge side and the cloud. Provide new solutions that are efficient, differentiated, low-cost, space-saving, and easy to maintain.

Description

technical field [0001] The present application relates to the technical field of industrial automation control, and more specifically, relates to an industrial intelligent control system based on software definition. Background technique [0002] The industrial intelligent control system is an important basis for the realization of intelligent manufacturing and intelligent factories. By building intelligent industrial control systems and networked industrial infrastructure, industrial production can be equipped with real-time control, independent decision-making, and system autonomy. The intelligent interaction and automation collaboration among them can improve the efficiency and intelligent level of industrial production. [0003] At present, there are mainly three types of industrial intelligent control implementation systems in existing technical solutions: (1) Adding AI modules to industrial controllers, this system can upgrade existing ordinary industrial controllers t...

AI Technical Summary

Problems solved by technology

[0003] At present, there are mainly three types of industrial intelligent control implementation systems in existing technical solutions: (1) Adding AI modules to industrial controllers, this system can upgrade existing ordinary industrial controllers to support industrial AI The application of intelligent controllers, but the interface adjustment between hardware is more complicated and difficult to transform; (2) On the general industrial server, use virtualization technology to realize the industrial control system that supports real-time and non-real-time task processing at the same time, the system can Realize the flexible and efficient allocation of hardware resources, but the implementation cost is relatively high; (3) AI controller, the system is equipped with an AI processor when the industrial controller is designed and manufactured, and can support industrial real-time control and industrial AI task processing at the hardware level , but lack of software platform support, poor isolation between real-time and non-real-time tasks, and low resource utilization

[0004] As a result, the implementation system of industrial intelligent control in the prior art has been unable to meet the business requirements and technical challenges of industrial intelligent control

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