AI Computing Node for Field Bus Closed-Loop Industrial Control
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Solution Overview
Problem
Traditional industrial controllers lack sufficient computing capacity and there is no flexible solution to integrate AI into industrial automation systems, limiting their control capabilities and efficiency.
Innovation Solution
An AI computing device with a field bus interface is introduced into the control loop of industrial automation systems, enhancing computing capacity and enabling real-time intelligent closed-loop control by analyzing production parameters and generating control instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If traditional industrial controllers are used, then the system structure is simple and existing equipment can be maintained, but the computing capacity is insufficient and control capability is limited
Solution Approach 1:
The system is divided into two independent parts: the traditional industrial controller and the AI computing device. The controller handles basic control functions while the AI device handles complex computing tasks, allowing each component to be optimized independently and resolving the contradiction between computing capacity and system complexity
Solution Approach 2:
A communication component serves as an intermediary between the controller and AI computing device, enabling data exchange without requiring direct integration. This mediator allows the system to gain enhanced computing capacity while maintaining the simplicity of the original controller structure
2Productivity
If AI computing device is added to enhance control capability, then control efficiency is improved, but device complexity increases
Solution Approach 1:
The AI computing device is designed with a field bus interface that enables it to integrate into existing industrial automation systems universally. It can work with multiple controller types and communication protocols, allowing enhanced control efficiency without requiring system-specific customization that would increase complexity
Solution Approach 2:
The AI computing device performs autonomous data analysis and generates control instructions independently. It receives raw data from the controller, processes it through AI algorithms, and returns optimized control instructions without requiring manual intervention, thereby improving control efficiency while adding only one self-contained component
3Adaptability or versatility
If existing controller is used, then device complexity is low, but adaptability to AI integration is poor
Solution Approach 1:
The field bus interface acts as an intermediary that translates between the existing controller's communication protocol and the AI computing device's data requirements. This allows the traditional controller to maintain its simple structure while the system gains AI integration capability through the added interface layer
Solution Approach 2:
AI integration functionality is segmented into a separate device rather than being embedded into the existing controller. This allows the controller to remain unchanged and simple, while the separate AI device provides the necessary adaptability for intelligent control applications
Data Source
AI summary
Provided is an artificial intelligence (AI) computing device applied to an industrial automation system. The AI computing device is connected to a field bus via a field bus interface and is communicated with a controller. The AI computing device processes data sent by the controller by using a built-in AI computing architecture, analyzes the data, and sends the analysis result to the controller. Also provided are a corresponding method and apparatus, an engineer station, and an industrial automation system.