Control Loop Variable Switching for Automated Decision Testing
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Solution Overview
Problem
Current automation systems are static and deterministic, lacking the ability to automatically vary control loop decisions, making it cumbersome, time-consuming, and expensive to test and implement changes, especially when dealing with complex scenarios.
Innovation Solution
A method and system that allow for the automatic variation of control loop decisions by defining and testing multiple variables over time, using a decision recipe to collect data, analyze results, and select optimized variations for improved performance and policy conformance, enabling non-deterministic operation and minimizing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automation systems use pre-defined deterministic actions, then the system operation is simple and predictable, but the system cannot automatically adapt or improve performance through variations
Solution Approach 1:
The patent transforms static deterministic automation into dynamic adaptive automation by introducing automatic variable substitution in control loop decisions. The system dynamically switches between different variable configurations based on performance feedback, enabling adaptability without manual intervention while managing complexity through automated experimentation.
Solution Approach 2:
The automation system performs self-optimization by automatically testing variable variations, collecting performance data, and implementing improvements without human intervention. This self-service capability allows the system to autonomously adapt and improve its own performance while maintaining operational simplicity.
2Productivity
If manual changes are made to test automation variations, then the system can evaluate different scenarios, but the process becomes time-consuming and expensive
Solution Approach 1:
The system automatically manages the entire experimentation process including variable substitution, data collection, performance evaluation, and implementation of improvements. This eliminates time-consuming manual operations while maintaining comprehensive testing capabilities, significantly improving productivity without sacrificing thoroughness.
Solution Approach 2:
The patent implements continuous feedback loops where performance data from variable variations is automatically collected, analyzed, and used to guide further experimentation. This automated feedback mechanism accelerates the testing process by eliminating manual analysis cycles and enabling rapid iteration through systematic performance monitoring.
3Manufacturing precision
If multiple variable variations are tested manually, then performance optimization is possible, but the complexity of setting up and managing variations increases significantly
Solution Approach 1:
The system autonomously manages the complexity of multiple variable variations by automatically generating, tracking, and evaluating different configurations. This self-management capability enables comprehensive performance optimization across multiple variables without requiring manual coordination, thereby maintaining precision while reducing operational complexity.
Solution Approach 2:
The patent breaks down the complex task of multi-variable optimization into manageable segments by testing variables systematically and evaluating their individual and combined effects. This segmented approach to experimentation makes complex variation management tractable through structured, modular testing procedures.
Data Source
AI summary
A method includes defining a plurality of variables to modify in a control loop; collecting first data using a first variable of the plurality of variables while executing the control loop, generating a first result based on the collecting first data step, substituting a second variable of the plurality of variables for the first variable, collecting second data using the second variable while executing the control loop, generating a second result based on the collecting second data step, comparing the first result and the second result; and taking an action based on the comparing step.