Dynamic Event-Triggered Data Exchange in Networked Vehicle Control
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Solution Overview
Problem
Existing networked multiagent systems face challenges in efficiently managing inter-agent information exchange to ensure closed-loop system stability while preventing network overload and reducing wireless communication costs.
Innovation Solution
An event-triggered distributed control architecture is implemented, utilizing a dynamic threshold based on an error signal and an exponentially decaying term to schedule information exchange, along with a solution-predictor curve to estimate future data exchange, reducing the frequency of inter-agent communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous information exchange is implemented among agents, then closed-loop system stability is ensured, but network overload and wireless communication costs increase
Solution Approach 1:
The patent implements event-triggered control where information exchange occurs periodically only when specific triggering conditions are met, rather than continuously. The event-triggering condition monitors system state changes and initiates communication only when necessary, thereby ensuring closed-loop stability while significantly reducing network utilization and wireless communication costs.
2Reliability
If frequent data exchange is performed, then system stability is maintained, but communication energy consumption increases
Solution Approach 1:
The patent employs feedback mechanisms through event-triggering conditions that continuously monitor system state variables. Communication is activated only when the feedback signal indicates a violation of the triggering condition, ensuring stability is maintained while minimizing unnecessary energy consumption from frequent transmissions.
Solution Approach 2:
The system uses periodic event-triggered sampling where data exchange occurs at intervals determined by system state changes rather than continuous periodic transmission. This reduces communication energy consumption while maintaining stability through strategically timed updates.
3Adaptability or versatility
If distributed control is implemented among multiple agents, then system coordination is improved, but communication complexity increases
Solution Approach 1:
The patent segments the multiagent system into independent agents that each execute local event-triggered control algorithms. Each agent autonomously determines when to communicate based on its own triggering conditions, reducing overall communication complexity while maintaining coordination through distributed decision-making.
Data Source
AI summary
Methods and systems for information exchange of a vehicle in a networked multiagent system are disclosed. The methods and systems include: receiving a last neighbor dataset broadcasted by a neighbor vehicle; determining a current dataset based on the last neighbor dataset and a last vehicle dataset of the first vehicle; identifying a violation of an event-triggering condition by comparing a difference between the last vehicle dataset and the current dataset with a dynamic threshold; determining a transmission dataset being associated with the current dataset; and in response to the violation, broadcasting the transmission dataset to the neighbor vehicle. The dynamic threshold is defined by an exponentially decaying term and an error between a vehicle state of the first vehicle and a reference state. Other aspects, embodiments, and features are also claimed and described.