Event-Based Adaptive Distributed Observer with a Positive Minimum Inter-Event Time

Reducing communication resource consumption and enhancing autonomy are critical challenges in advancing the engineering application of distributed state estimation, while the event-based communication and fully distributed design are potential solutions to realize these goals. This paper tackles a class of event-based fully distributed state estimation problems with positive minimum inter-event time (MIET) and provides a framework of node-based adaptive distributed event-triggered strategy for the networked system to cooperatively estimate the target system state. First, by introducing robust adaptive laws and corresponding event-triggered mechanisms (ETMs), an event-based robust adaptive distributed observer is designed, which allows each agent to effectively reconstruct the target system state using partial measurement output information and event-based interaction information in the presence of measurement disturbances, without relying on any global information. Second, in order to accurately estimate the target system state in the absence of measurement disturbances, an event-based adaptive distributed observer is proposed, ensuring that the estimation error could asymptotically converge to zero. Moreover, each ETM proposed in these two event-based distributed observers guarantees a strictly positive MIET separately, effectively excluding Zeno behavior in direct proofs. Finally, the effectiveness of the proposed observers is illustrated through several simulation examples.