Model-Based Control Platform for Industrial Automation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The use of model-based control techniques in industrial control platforms is limited, requiring repetitive programming scripts, compilation tools, and code generation processes, which are time-consuming and require additional skilled workforce, hindering efficient control performance improvements.
Innovation Solution
A model-based control platform that includes a processor, memory, component model library, model-based analytic algorithm library, and a control definition sub-unit to obtain and interconnect component models and algorithms, generating a model-based control solution without the need for low-level programming or code generation, using a validation subsystem to simulate and deploy the solution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If model-based control techniques are implemented in industrial control platforms, then control performance is improved, but development time and complexity increase due to repetitive programming scripts, compilation tools, and code generation processes
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical industrial asset that includes a mathematical model of the asset's behavior. This digital twin can be used for simulation, analysis, and control without affecting the actual asset, enabling model-based control techniques to be developed and tested virtually before deployment, thereby reducing development time while maintaining control performance improvements.
Solution Approach 2:
The patent performs model-based control development, simulation, and validation in advance using the digital twin before deploying to the actual industrial asset. By conducting preliminary actions in the virtual environment, the patent eliminates the need for repetitive programming and code generation during actual deployment, reducing development time while preserving control performance benefits.
2Reliability
If model-based control techniques are implemented in industrial control platforms, then control performance is improved, but the process requires additional skilled workforce and low-level programming expertise
Solution Approach 1:
By creating a digital twin that replicates the physical asset's behavior, the patent enables control engineers to work with virtual models rather than requiring low-level programming expertise. The digital twin abstracts the complexity, allowing engineers to apply model-based control techniques without needing deep knowledge of compilation tools and code generation processes.
Solution Approach 2:
The digital twin acts as an intermediary between the control engineer and the physical asset. It provides a simplified interface for implementing model-based control techniques, translating high-level control strategies into actionable commands without requiring engineers to directly program low-level control code, thereby reducing workforce skill requirements while maintaining control performance.
3Adaptability or versatility
If traditional PLC programming methods are used with primitive modules, then flexibility and ease of modification are maintained, but model-based control techniques cannot be effectively implemented
Solution Approach 1:
The patent creates a universal platform that combines the flexibility of traditional PLC programming with the capabilities of model-based control techniques. The digital twin framework can accommodate both primitive module-based control and model-based control approaches, allowing engineers to leverage the adaptability of PLC systems while implementing advanced control techniques that improve performance.
Solution Approach 2:
The patent segments the control system into distinct layers: the digital twin layer for model-based control development and simulation, and the execution layer for actual control implementation. This segmentation allows model-based control techniques to be developed independently in the virtual environment while maintaining the flexibility and ease of modification characteristics of traditional PLC systems in the execution layer.
Data Source
AI summary
A method for building a model-based control solution is disclosed. The method includes obtaining, via a model-based control definition sub-unit, a first set of component models from a component model library and defining, via the model-based control definition sub-unit, a system model by interconnecting the first set of component models. Also, the method includes obtaining, via the model-based control definition sub-unit, a first model-based analytic algorithm from a model-based analytic algorithm library and associating, via the model-based control definition sub-unit, the first model-based analytic algorithm with the system model to generate the model-based control solution.