Distributed Control System Simulation for PLC Execution Time Optimization
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Solution Overview
Problem
Distributed control systems face challenges in maintaining real-time performance due to the introduction of cloud computing, which can lead to suboptimal operation allocation among programmable logic controllers (PLCs) in large-scale control systems.
Innovation Solution
A distributed control system that includes a communication network with control devices equipped with simulators, shared memory, and a simulation table database to simulate and allocate program organization units among PLCs, optimizing execution efficiency and load distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud computing is introduced to distribute loads to local systems, then system scalability and resource utilization are improved, but real-time performance deteriorates
Solution Approach 1:
The control system is segmented into local control devices (PLCs) that execute control programs locally and a cloud-based platform that handles non-real-time monitoring and management functions. This segmentation allows real-time control to remain at the edge while leveraging cloud resources for scalability.
Solution Approach 2:
A communication network acts as an intermediary between the cloud computing platform and local control devices, enabling load distribution while maintaining real-time performance through optimized data transmission protocols and buffer mechanisms.
2Ease of manufacture
If operation allocation is entrusted to designers in conventional local control systems, then system implementation is simplified, but operation allocation optimality deteriorates
Solution Approach 1:
The system performs preliminary simulation of control programs on target PLCs before actual deployment. This preliminary action allows automatic generation of optimized operation allocation based on simulated performance data, eliminating the need for manual designer optimization while maintaining simplicity in implementation.
Solution Approach 2:
The system incorporates feedback loops where simulation results from control program execution are automatically analyzed and used to refine operation allocation. This closed-loop approach enables continuous optimization without requiring expert designer intervention.
3Loss of time
If control programs are executed on PLCs without simulation, then system deployment is faster, but execution efficiency optimality deteriorates
Solution Approach 1:
Control programs are simulated on target PLCs during the deployment phase to measure execution times and identify performance bottlenecks. This preliminary simulation enables optimization of program allocation before actual operation, ensuring optimal execution efficiency from the start.
Solution Approach 2:
The system dynamically adjusts allocation parameters based on simulation results, matching control programs to PLCs with compatible processing capabilities and optimal performance characteristics. This parameter optimization ensures efficient execution without sacrificing deployment speed.
Data Source
AI summary
According to one embodiment, a distributed control system comprises a communication network and a plurality of control devices configured to control devices to be controlled, respectively. The control devices each include a simulator to which a program organization unit is allocated in advance, configured to simulate the allocated program organization unit, and a shared memory that stores a simulation result of the program organization unit simulated by the simulator to be shared with another control device. At least one of the control devices includes a simulation table database that can store therein an execution time of each of the program organization units allocated in advance to the control devices, and a simulation commander that stores, in the simulation table database, the execution time of each of the program organization units corresponding to the simulation result.