Industrial Controller Optimization Using Scan-Based Execution
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Solution Overview
Problem
Industrial controllers lack the capability to execute mathematical optimization functions using their native processing resources, necessitating offloading to external platforms, which increases complexity and introduces security concerns.
Innovation Solution
An industrial controller equipped with a program execution component and an optimization component that executes optimization routines using scan-based processing, allowing local execution of optimization algorithms within the controller.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If optimization routines are executed on external computing platforms (Windows or Linux), then mathematical optimization functions can be performed, but system complexity increases and security concerns arise
Solution Approach 1:
The patent merges the optimization functionality with the industrial controller by integrating an optimization engine directly into the controller's processing unit. This allows the controller to execute both control logic and optimization routines locally, eliminating the need for separate external computing platforms and reducing system complexity while maintaining optimization capabilities
Solution Approach 2:
The industrial controller is designed to perform multiple functions: traditional control logic execution and mathematical optimization. By making the controller universal, it can handle both control and optimization tasks within a single device, reducing the need for additional external systems and simplifying the overall architecture
2Adaptability or versatility
If optimization routines are executed on external computing platforms, then mathematical optimization functions can be performed, but security concerns arise due to potential security gaps in optimization tools
Solution Approach 1:
By combining optimization functionality directly within the industrial controller, the system eliminates security vulnerabilities associated with external communication interfaces and third-party optimization tools. The integrated approach ensures that optimization routines execute in the same secure environment as control functions, maintaining industrial security standards
3Adaptability or versatility
If optimization routines are executed using external tools, then mathematical optimization can be achieved, but data exchange complexity and potential failure points increase
Solution Approach 1:
The integration of optimization routines within the controller eliminates data exchange interfaces between control and optimization systems. By processing optimization locally, the system removes communication protocols, data mapping layers, and external interfaces that could introduce failure points, thereby improving reliability
4Reliability
If scan-based processing is used for both control and optimization, then primary control functions are maintained, but processing resources must be shared
Solution Approach 1:
The system dynamically manages processing resources by implementing priority-based execution within the scan cycle. Control functions are assigned higher priority to ensure deterministic response, while optimization routines execute during lower-priority time slots. This dynamic resource allocation allows both control and optimization to share processing resources effectively without compromising control performance
Data Source
AI summary
An industrial controller can perform multi-dimensional optimization locally using the controller's native hardware and processing. An optimization algorithm is encoded on the industrial controller in a language understandable and executable by the controller (e.g., IEC61131-3). The optimization algorithm is adapted for the scan-based processing performed by industrial controllers rather than sequential processing, thereby allowing the optimization algorithm to be executed by the industrial controller as part of the controller's control program execution. A control program development system allows a user to add and configure the optimization algorithm as an instruction within the controller's control program. The instruction's configurable parameters allow the user to submit constraints and cost functions for the algorithm. During runtime, the controller executes this optimization instruction in accordance with the optimization parameters submitted by the user during development, using values of specified data tags as inputs and outputs for the algorithm.