Distributed Process Control with External Computing Units
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Solution Overview
Problem
Existing distributed process control systems face limitations due to the limited computing power of local automation units, making it difficult to implement complex control strategies like model predictive control, and require costly additional hardware and maintenance for expansions and optimizations.
Innovation Solution
A system that connects local automation units with external computing units via distributed communication mechanisms, allowing for complex calculations and simulations to be performed remotely, enabling cost-effective expansions and optimizations without additional on-site hardware, and allowing for dynamic adaptation of control parameters based on real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex control strategies like model predictive control are implemented in local automation units, then control precision and process optimization are improved, but device complexity and computing power requirements increase beyond what local units can provide
Solution Approach 1:
A cloud-based control unit acts as an intermediary between local automation units and the control strategy. The cloud unit receives process data from local units via OPC UA interface, executes complex model predictive control algorithms remotely, and sends control commands back to local units. This mediator approach enables advanced control precision without overloading local automation units with excessive computing requirements.
2Adaptability or versatility
If additional hardware is installed on-site to expand automation functions, then automation capabilities are improved, but device complexity and maintenance requirements increase
Solution Approach 1:
Instead of physically installing additional automation hardware on-site, the system creates a virtual copy of the control unit in the cloud. This virtual control unit replicates the functionality of physical controllers but runs remotely on cloud infrastructure. The local automation units maintain their original hardware configuration while gaining extended capabilities through connection to the cloud-based control unit via standard communication protocols.
3Manufacturing precision
If process engineering processes are automated in the higher-level monitoring system, then control precision is improved, but response time and operational efficiency worsen due to centralized processing bottlenecks
Solution Approach 1:
The control system is segmented into multiple levels: local automation units handle real-time monitoring and basic control tasks with immediate response, while the cloud-based control unit handles complex process engineering processes and optimization algorithms. This segmentation allows time-critical operations to be executed locally without waiting for centralized processing, while still benefiting from advanced control precision when the cloud unit provides updated control strategies.
Data Source
AI summary
The invention relates to a system (100) for controlling a process (1), comprising at least one automation unit (2) on the plant side, which performs a number of first process parameter calculations (10) and acts on the process (1) and is connected via a first data connection (4) to a monitoring system (5) for controlling and/or monitoring the process (1). The system further comprises an external computing unit (6) to which at least one automation unit (2) is connected via distributed communication mechanisms and with which it exchanges data via a second data connection (14). The external computing unit (6) performs a number of second process parameter calculations (11), which become effective in the process via the automation unit (2). The invention further relates to a method for extending at least one plant-side automation unit (2) to the aforementioned system (100).