Co-Regulating Communication For Asynchronous Information Consensus

Muti-agent consensus controllers typically use discrete communication and hence are restricted to fixed-rate or event-triggered communication. Fixed-rate communication suffers from inefficient use of communication and computational resources but is easy to implement, while event-triggered communication conserves resources but suffers from the ambiguity of all event-triggered systems-inability to distinguish failure from lack of new information. We propose a novel hybrid strategy of co-regulating communication with state disagreement amongst the agents obtaining the benefits of discrete fixed-rate and event-triggered consensus while mitigating the associated disadvantages. Our approach dynamically adjusts the communication rate in response to disagreement in the shared state variable, resulting in a discrete-time-varying, asynchronous network topology. We prove convergence properties of the proposed consensus algorithm, develop metrics to evaluate similar dynamic approaches, and demonstrate the results in simulation, showing our algorithm reduces communication resources, while maintaining fast convergence time.