Intelligent Conversion Method from Function Block Diagram to Instruction List Based on AOV Diagram and Series-Parallel Merge Algorithm
In the programmable logic controller programming tool software, the conversion from function block diagram to instruction list plays an important role. Aiming at the problems of the existing algorithm for converting PLC multi-output function block to instruction list, an algorithm for intelligent co...
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| Published in: | Chinese Control Conference pp. 2586 - 2591 |
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| Main Authors: | , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
Technical Committee on Control Theory, Chinese Association of Automation
24.07.2023
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| Subjects: | |
| ISSN: | 1934-1768 |
| Online Access: | Get full text |
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| Summary: | In the programmable logic controller programming tool software, the conversion from function block diagram to instruction list plays an important role. Aiming at the problems of the existing algorithm for converting PLC multi-output function block to instruction list, an algorithm for intelligent conversion from function block to instruction list based on AOV directed graph is proposed. This algorithm strictly follows the IEC61131-3 standard, uses JSON format to store function block programs, and then maps the function blocks and its connection relationships to AOV directed graphs by analyzing the storage files. Afterwards, we proposed an improved algorithm based on the series-parallel merge scan algorithm and the multi branch logic tree, which decomposes complex functional block diagrams and adds auxiliary nodes at branch points to construct the multi branch logic trees. Then, an instruction list is generated based on the multi branch logic trees. Practical applications have shown that this algorithm improves conversion efficiency and accuracy without increasing algorithm complexity, and can be well applied to multi output control programs. This algorithm can be applied to automated production lines based on PLC process control, and is also applicable to various industrial control scenarios. |
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| ISSN: | 1934-1768 |
| DOI: | 10.23919/CCC58697.2023.10240222 |