Equation Editor for Chemical Process Model Development
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Solution Overview
Problem
Conventional process control systems require specialized knowledge and are time-consuming for engineers to develop and maintain models of complex chemical processes, especially non-linear models, due to the need for knowledge of specific modeling languages and software integrations, making it challenging for users without expertise in chemical engineering.
Innovation Solution
A system and method using an equation editor for process control that allows users to input chemical engineering equations graphically, generating model information and an equation stack, which is evaluated by an equation evaluation engine to provide results to the process controller, facilitating model-based control and optimization without requiring knowledge of modeling languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional process control systems use traditional modeling approaches, then model accuracy can be achieved, but the complexity of model development and maintenance increases significantly
Solution Approach 1:
The patent introduces an equation evaluation system as an intermediary between the process control system and the mathematical models. This system includes an equation editor that accepts user-friendly equation inputs, a model factory that processes these equations into executable formats, and an equation evaluation engine that solves the equations. This intermediary layer shields users from the complexity of traditional modeling while maintaining model accuracy through rigorous mathematical evaluation.
Solution Approach 2:
The system enables self-service model development through its equation editor interface, which allows users to input process equations using standard mathematical notation without requiring expertise in specialized modeling languages. The model factory automatically processes these inputs into executable models, and the evaluation engine solves them, allowing users to develop and maintain models independently without needing deep chemical engineering or modeling expertise.
2Manufacturing precision
If specialized modeling languages are used for process control, then precise model representation is achieved, but the ease of operation decreases due to the need for specialized knowledge
Solution Approach 1:
The system segments the complex modeling process into distinct, manageable components: an equation editor for input, a model factory for processing, and an evaluation engine for solving. Each component handles a specific aspect of model development, allowing users to interact with only the equation editor using familiar mathematical notation, while the other components automatically handle the translation and solution processes.
Solution Approach 2:
The equation evaluation system serves multiple functions within a single integrated platform: it accepts various types of process equations (mass balance, energy balance, kinetic equations), automatically processes them into executable formats, and solves them for different control applications. This universal approach allows users to work with diverse process models using a single interface, eliminating the need to learn multiple specialized modeling languages.
3Reliability
If detailed process models are developed for accurate control, then control performance is improved, but the time required for model development increases
Solution Approach 1:
The model factory performs preliminary actions by automatically processing and pre-compiling user-input equations into executable model formats before they are needed for control operations. This pre-processing step includes validating the equations, converting them into the appropriate mathematical representations, and preparing them for efficient evaluation, thereby reducing the time required during actual control operations and model iterations.
Solution Approach 2:
The equation evaluation engine enables continuous model evaluation and control optimization by efficiently solving process equations in real-time. The system maintains continuous operation by rapidly evaluating models as process conditions change, allowing for ongoing control adjustments without requiring repeated model development cycles. This continuous evaluation capability maintains high control performance while minimizing the time investment needed for model development.
Data Source
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AI summary
A system a process controller (102, 202, 302) and an equation evaluation apparatus. The equation evaluation apparatus includes an equation editor (221, 321), a model factory (324), and an equation evaluation engine (214, 318). The equation editor is adapted to receive equations describing a process (104, 204) to be controlled by the process controller. The equation editor is also adapted to generate model information (223, 323) representing the equations. The model factory is adapted to receive the model information and generate an equation stack (316) representing the equations. The equation evaluation engine is adapted to receive evaluation information (220, 320) from the process controller, evaluate at least one of the equations using the evaluation information and the equation stack, and send a result of the evaluation (222, 322) to the process controller. The model information could include information representing algebraic equations, differential equations, algebraic states, differential states, inputs, parameters, constants, and/or expressions.