Decentralized Flow Control Using Local Buffer-Based Rule Adjustment
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Solution Overview
Problem
Existing flow control systems face high introduction and control costs due to the need for centralized information gathering and complex prediction in uncertain environments, leading to inefficiencies and increased costs, especially in production and traffic management systems.
Innovation Solution
A decentralized flow control system where work units α and β are linked, with α units having independent control objectives and rules, and β units dynamically adjusting control rules based on partial information to achieve α objectives, reducing the need for comprehensive data collection and minimizing costly over-control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized information gathering and complex prediction are implemented to achieve precise flow control, then control precision is improved, but device complexity and introduction costs increase
Solution Approach 1:
The patent divides the flow control system into multiple independent work units (α and β units), each capable of autonomous decision-making based on local buffer information. This segmentation eliminates the need for centralized information gathering and complex system-wide prediction, reducing device complexity while maintaining control precision at the local level.
Solution Approach 2:
Each work unit is equipped with local control capabilities that enable it to make decisions based on its own buffer status and local conditions. The β units dynamically adjust control rules based on partial local information, achieving precise flow control without requiring global system information, thus reducing overall system complexity.
2Reliability
If comprehensive data collection is performed to prevent buffer overflow and starvation, then reliability is improved, but loss of time and control costs increase
Solution Approach 1:
The system pre-establishes control rules and decision-making algorithms in each work unit before operation begins. When buffer levels reach critical thresholds, work units can immediately execute pre-programmed responses without requiring time-consuming data collection and analysis, thus preventing buffer overflow and starvation while minimizing time loss.
Solution Approach 2:
Each work unit autonomously monitors its own buffer status and makes control decisions based on local information, eliminating the need for time-consuming centralized data collection. The β units self-adjust control rules based on partial local information, achieving reliable buffer control with minimal time investment.
3Adaptability or versatility
If dynamic control rule adjustment based on partial information is implemented, then adaptability is improved, but measurement precision requirements increase
Solution Approach 1:
The β work units adjust control rules based on partial local information rather than requiring complete and highly precise system-wide data. This partial action approach enables dynamic adaptability to changing conditions while reducing the stringent measurement precision requirements that would be necessary for comprehensive system monitoring.
Data Source
AI summary
This flow control system is obtained by connecting a plurality of work units WUα and a plurality of work units WUβ to one another, wherein: each WUα has an α-control purpose which is a WU-based independent control purpose, and has an α-control rule for the α-control purpose; each WUβ has a β-control purpose to cause as many WUα as possible to achieve the own α-control purposes, and has a β-control rule for the β-control purpose; the β-control rule is dynamically changed on the basis of partial information about the flow control system; and the WUβ is disposed in a part of the flow control system.