Adaptive hybrid synchronisation in uncertain Kuramoto networks with limited information
S Baldi (TU Delft - Team Bart De Schutter)
Tian Tao (TU Delft - Team Bart De Schutter)
Elias B. Kosmatopoulos (Centre for Research and Technology Hellas, Democritus University of Thrace)
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Abstract
In this study, the authors study adaptive synchronisation in networks with Kuramoto units whose parameters are unknown and where measurements are quantised over the communication network (therefore information is limited). They show that, for an undirected connected graph, synchronisation is enabled via appropriate adaptive protocols that counteract the effect of heterogeneity, uncertainty and quantised information. In particular, to address heterogeneity and uncertainty, appropriate adaptive laws are designed to drive the network to frequency synchronisation; to address quantised information, a dynamic quantiser is introduced and embedded into the adaptive mechanism via a zooming-based approach (therefore with hybrid dynamics). The resulting protocol ends up being an adaptive hybrid synchronisation strategy that can be distributed throughout the network: the quantiser is co-designed with the controller, as typical for zooming-based quantisation. The proposed integrated adaptation+quantisation protocol guarantees asymptotic synchronisation to a desired frequency, which is shown via an appropriately designed distributed Lyapunov function. Numerical simulations are also used to demonstrate the effectiveness of the proposed protocol.