Distributed state estimation and optimal control for networked systems with correlated data dropouts over slow-fading channels: an experimental evaluation

This study examines a distributed architecture in which heterogeneous nodes collaboratively handle sensing, estimation, and control tasks for a shared system. In this framework, data transmitted over unreliable wireless channels may experience packet losses, which can be temporally correlated when the channel undergoes a phenomenon known as fading. In this work, we propose a consensus-based distributed estimation method combined with a stabilising optimal control law that accounts for the temporal correlation of packet drops. We also analyse the boundedness, convergence, and asymptotic behaviour of our algorithm, while investigating both upper and lower bounds for the error covariance associated with the proposed estimation and control algorithms. Furthermore, we have conducted numerical simulations and developed an experimental test-bed using software-defined radios to validate the findings.